Download Interest Rate Channel in Indonesia during Inflation - UvA-DARE

Universiteit
Van
Amsterdam
Faculty
of
Economics
and
Business
MSc
Economics
MASTER
THESIS
Interest
Rate
Channel
in
Indonesia
during
Inflation
Targeting
Era
Author:
Wulan
Widyasari
Mantik
Student
Number:
6260462
Supervisor:
Dr.
A.
Ormeño
Sanchez
1
Table of Contents
Chapter
1............................................................................................................................................................... 4
INTRODUCTION ................................................................................................................................................. 4
1.1
Background.............................................................................................................................................. 4
1.2.
Problem
Statement.............................................................................................................................. 5
1.3
The
Organization
of
Writing............................................................................................................. 6
Chapter
2............................................................................................................................................................... 7
THEORY
AND
LITERATURE
REVIEW....................................................................................................... 7
2.1
Inflation
Targeting................................................................................................................................ 7
2.1.1
Why
Inflation
Targeting? .......................................................................................................... 7
2.1.2
What
is
Inflation
Targeting? ..................................................................................................10
2.1.3
How
Does
Inflation
Targeting
Work? ................................................................................11
2.1.4
Has
InflationTargeting
Mattered? .......................................................................................12
2.2
Interest
Rate
Channel........................................................................................................................18
2.2.1
The
Importance
of
Interest
Rate
Channel........................................................................18
2.2.2
Determinant
of
Interest
Rate
Pass‐Through ..................................................................21
2.2.3
Evidence
on
Interest
Rate
Pass‐Through.........................................................................23
3.1
The
Adoption
of
Inflation
Targeting ...........................................................................................25
3.2
Interest
rate
channel .........................................................................................................................28
Bibliography ......................................................................................................................................................31
2
List of Tables
Table 1: Inflation Targeting Countries in the World, 1990-2008 ........................................... 35
Table 2: Measures of Inflation Deviations from Targets and Inflation Deviations in IT
Countries, from IT Starting Quarter through 2008IV ............................................................. 36
List of Figures
Figure 1: Central Bank Transparency Index for Country Groups by Monetary Policy
Regimes, 1998-2006 ............................................................................................................... 38
Figure 2: Central Bank Transparency Index for Industrial and EME IT Country Groups,
1998-2005 ............................................................................................................................... 38
3
Chapter 1
INTRODUCTION
1.1 Background
Monetary policy consists of rules and actions that are used by central banks to achieve their
objective. Many central banks around the world have put more attention on the importance of
having a stable price level so they set price stability as their ultimate objective. High level of
uncertainty on inflation rate is not desirable because it could hamper economic growth of a
country through its effects on households’ and firms’ decisions to consume and invest. Price
stability enables households and firms to easily identify the changes in the relative price of
various goods and services so that they will not misinterpret changes in general price level as
changes in the relative price. As a result, they have better information to make investment
and consumption decisions (ECB , 2000).
In order to achieve price stability, many central banks changed their policy instruments or
redesigned their monetary operating procedures, involving the transmission mechanism of
monetary policy. The monetary transmission mechanism is a process in which a change in
monetary policy affects inflation and real economy. Monetary transmission mechanism
consists of various channels, namely interest rate channel, exchange rate channel, credit
channel, asset prices channel, and expectation channel. Most central banks usually choose
interest rate as their policy instrument. Changes in the policy rate will first have effects on
changes in short-term interest rates and then will be followed by changes in the deposit and
loan rates. Eventually these changes will affect investment and consumption decisions by
firms and households. With some lags, the level of investment and consumption will
determine the level of output and price. The worldwide emergence of using short-term
interest rates as the main instrument of monetary signals has made the interest rate channel
the key transmission channel.
Bank Indonesia (BI), the central bank of Indonesia, has also realized the importance of price
stability. It is stipulated in the Act no 23/1999 that the sole and ultimate objective of BI is to
achieve and maintain the stability of the rupiah. The Act also outlines a clear mechanism for
accountability and transparency of monetary policy that could be achieved through, inter alia,
announcing annual inflation target. The Act brought a substantial change to the conduct of
4
monetary policy after the country was hit by a severe crisis in 1997. The crisis resulted in the
abandonment of the unsustainable, rigid rupiah. As the rupiah became freely floating, BI
needed to choose a new nominal anchor. BI then decided to turn to a new approach by using
the inflation rate as a nominal anchor. Following such a decision, and with the mandate of the
new act, BI decided to announce its annual inflation target, starting at the beginning of 2000.
This action became the initial step towards the adoption of inflation targeting (IT)
framework. However, the official launching of IT as BI’s new monetary policy framework
only took place in July 2005.
As a preparation towards the adoption of a formal or a full-fledged IT framework, BI
conducted comprehensive research on the key transmission channels, including the interest
rate channel. Kusmiarso, Sukawati, Pambudi, Angkoro, Prasmuko, and Hafidz (2002)
measure the significance of interest rate channel in influencing inflation for both the precrisis and post-crisis periods. For the pre-crisis period, interest rate channel performed quite
well to influence interest rates for deposits and lending, but was not effective enough in
affecting consumption and investment due to the abundant foreign capital inflows. Interest
rate channel still showed a good performance during the post-crisis period, although its
strength was influenced by the conditions of the banking system and the overall higher
uncertainty. Earlier studies also reveal that interest rate channel is strong for the pre-crisis
period and recommend the use of the interest rate as the operational target for monetary
policy (Boediono, 1998, Sarwono & Warjiyo, 1998, Warjiyo & Zulverdi , 1998). However, it is
unknown whether interest rate channel is still performing well after the adoption of IT
framework in Indonesia. This leave room to conduct a literature study to assess this issue.
1.2. Problem Statement
In the previous section, the motivation behind this research is described. To summarize, there
is still a void of research about the performance of interest rate channel after the adoption of
IT framework in Indonesia. This interest rate performance can be measured by the strength of
interest rate pass-through, i.e. the pass-through of money market interest rates to retail
interest rates. Retail interest rates consist of deposit rates and lending rates. This paper aims
at answering the research question of “Does the pass-through to deposit and lending rates
remain strong after the adoption of IT framework in Indonesia?” by conducting a literature
study.
5
1.3 The Organization of Writing
1. Introduction
1.1 Background
1.2 Problem Statement
1.3 The Organization of Writing
2. Theory and Literature Review
2.1. Inflation Targeting
2.1.1 Why Inflation Targeting?
2.1.2 What is Inflation Targeting?
2.1.3 How Does Inflation Targeting Work?
2.1.4 Has Inflation Targeting Mattered?
2.2. Interest Rate Channel
2.2.1 The Importance of Interest Rate Channel
2.2.2 Determinant of Interest Rate Pass-Through
2.2.3 Empirical Evidence on Interest Rate Pass-Through
3. Monetary Policy in Indonesia
3.1. The adoption of Inflation Targeting Framework
3.2. Interest Rate Channel
4. Analysis
5. Concluding Remarks
6
Chapter 2
THEORY AND LITERATURE REVIEW
This chapter is divided into two sections. The first section aims to provide the theory and
evidences on IT. The theory about IT includes the background of IT adoption, the definition
of IT, and the implementation of IT. This part also shows some empirical evidences
regarding IT successfulness in achieving price stability and improving macroeconomic
conditions. The second section discusses the importance of interest rate channel, the
determinants of interest rate pass-through, and some evidences on the performance of interest
rate pass-through.
2.1 Inflation Targeting
The collapse of the Bretton Woods System in 1971 had spread the search for a new monetary
policy framework. In 1990, New Zealand pioneered a new approach to monetary policy that
is based on reaching a specific inflation target. This approach was later known as inflation
targeting (IT). Within two decades from its first introduction, IT has gained 28 followers
(Schmidt-Hebbel, 2009). As shown by Table
1, among these countries, about half of them are
developing and emerging-market economies. In addition, many advanced countries like the
U.S., Japan, and the Eurozone accepted many attributes of IT while some other countries are
on their way to adopt IT (Roger, 2010).
2.1.1 Why Inflation Targeting?
A low and stable inflation is important in creating a well-functioning economy because the
costs of high inflation are pretentious. High inflation could dampen the level of output
through, among other things, its influence on saving and investment decisions by households
and firms. This happens because households and firms take into account the expected future
price when making a decision. As high rates of inflation entail high variability of inflation,
any unexpected disinflation will make these decisions subject to higher risks (Freedman &
Laxton, 2009). When a firm finance long-term investment with long-term debt, for example,
and an unexpected disinflation takes place, this firm is prone to the risk of losses. Moreover,
high and unstable inflation may cause households and firms making wrong investment or
7
consumption decisions. This happens because they have difficulties in distinguishing relative
price changes, i.e. the prices of goods in terms of other goods, from the general price.
A period of high inflation is also likely to induce asset price bubbles, although it is not
always the case that these bubbles occur at times of inflation. During the period of high
inflation, it is difficult to measure the developments of future asset prices, and thus these
assets tend to be overvalued. As a result, price bubbles may occur. The serious costs that are
imposed by high inflation has made monetary authorities around the world become more and
more alert to the significance of achieving and maintaining price stability (Freedman &
Laxton, 2009). Moreover, as generally economists agree that monetary policy can affect real
quantities, like output and unemployment, only in the short run, choosing inflation as the
main objective becomes more convincing when medium- to long-term horizons are
considered (Bernanke & Mishkin, 1997).
In pursuing a low and stable inflation rate, central banks usually choose a nominal anchor.
Freedman and Laxton (2009) explain why a nominal anchor can bring many merits to the
conduct of a monetary policy. First, a nominal anchor is very useful in helping central banks
to stay focus on the main objective and not to astray to very different objectives that may be
proposed by the monetary policy decision makers. Second, a publicly announced nominal
anchor will give clarity to the public about central bank’s objective in choosing a policy
action and the reason behind a change in policy instrument. Finally, a credible nominal
anchor is helpful in keeping public’s expectations ally with the policy goal, and therefore
expedites the goal’s accomplishment.
In the past, the monetary aggregate was common to be used as a nominal anchor.
Unfortunately, targeting monetary aggregate was found to be ineffective due to the unstable
money demand function (Bernanke & Mishkin, 1997). Moreover, according to Roger (2010),
monetary targeting has not been successful because of financial market innovations. From the
1980s on, the emergence of financial globalization has made monetary targeting increasingly
difficult. Besides money targeting, many countries chose to tie their domestic currency to a
major currency as to achieve the similar low rates of inflation with the chosen major
currency. It means that the exchange rate was used as nominal anchor. However, in the first
8
half of 1990s, many countries that opted for fixed exchange rate, such as Indonesia, Thailand,
the U.K., Sweden, and Finland, were put under market pressure. As a result, they had to
abandon the fixed exchange rate regime. Since the exchange rate could no longer be used as a
nominal anchor and since the monetary aggregate was likely lacking of stability, these
countries had to choose an alternative nominal anchor. Their choice fell to the sole sound and
available option, which was IT. Hammond (2010) sees this as a pragmatic reason for
adopting IT. He argues that the adoption of IT is mainly due to a failure in other monetary
regimes rather than an advance in theory. However, Mishkin (2000) argues that IT is
predominant from monetary targeting because it does not rely on the stability of the
relationship between money and inflation. IT basically utilizes all the available information to
choose the best settings for the monetary policy instruments. Furthermore, IT is also more
advantageous from exchange rate peg. This is because IT could respond to shocks to the
domestic economy well.
In nearly all cases, the intention to achieve and maintain a lower rate of inflation has been the
driving factor for a country to adopt IT (Freedman & Laxton, 2009). The economic
conditions surrounding the adoption of IT, however, varied from country to country. New
Zealand and Canada, the inflation targeter pioneers, chose to adopt IT not because their
economy was in a crisis. They switched to IT mainly because they found IT best suited their
needs of having a framework that could operate well in achieving price stability under a
flexible exchange rate and unstable monetary aggregates. In some cases, like in the U.K.,
Sweden, and Brazil, the adoption was a result of the abandonment of the fixed exchange rate
regime. As the exchange rate became more flexible, they need to choose an alternative
nominal anchor. Against the background of unstable monetary aggregates, they considered IT
framework as the best available mechanism. In other countries like Chile and Israel, IT
adoption occurred gradually. In the beginning, they combined IT with the existing exchange
rate target but along the time they put increasingly emphasis on IT.
In addition, the reason why more and more countries chose to adopt IT is because IT is
associated with increased transparency of monetary policy and increased accountability of the
monetary policy makers. An explicit quantitative target of inflation brings about transparency
because it communicates a clear and understandable goal for monetary policy. As the
monetary policy becomes more transparent, central bank will likely be more committed in
meeting its target, and thus improving accountability of the central bank. Both transparency
9
and accountability are important in enhancing the credibility of monetary policy. A credible
monetary policy is crucial because it helps to anchor public’s expectations about current and
future inflation.
2.1.2 What is Inflation Targeting?
Inflation targeting is defined as a framework of monetary policy which consists of four main
elements: (1) public announcement of inflation target over a specified time horizon (inflation
target serves as nominal anchor); (2) explicit pursuit of a low and stable inflation as a primary
and long-term goal, to which other goals are subordinated; (3) a more transparent central
bank through conducting good communication to the public about the chosen plans,
objectives, and decisions; (4) central bank’s accountability in achieving those objectives
(Bernanke, Laubach, Mishkin, & Posen, 1999, Mishkin, 2000). Mishkin (2000) adds one
critical element to that definition. He argues that IT should be supported by an information
inclusive strategy that will determine the settings of policy instrument. This strategy should
contain many variables and not only monetary aggregates or the exchange rate. He underlines
that IT is not merely about announcing inflation target for the year ahead, but also having the
other four aforementioned elements in the monetary policy strategy as to assure IT will be
sustainable over the medium term.
The above definitions are based on so-called full-fledged IT. However, there are many
countries that perform “lighter” versions of IT either as a preparation towards full-fledged IT
or to avoid the implications brought by the commitment to IT (Stone, 2003). IT, for example,
was initially used by Chile and Israel in tandem with exchange rate regime but gradually
increased the domination of inflation targeting regime. There is also other version in which a
country is not as transparent as the general inflation targeters in communicating their strategy
to the public.
For the successfulness of IT adoption and maintaining, inflation targeter candidates should
beforehand assess whether they have met several prerequisites. These prerequisites include
the absence of fiscal and finance dominance, moderately low level of inflation, and central
bank independence (Mishkin & Savastano, 2000,
Mishkin & Schmidt-Hebbel, 2007).
Central bank independence includes goal independence and instrument independence. Goal
independence means that central bank is independent in formulating objectives, whereas
10
instrument independence implies the independence of central bank in choosing the
instruments with which to achieve the chosen inflation target. In addition, it is also necessary,
albeit not mandatory, to increase technical capability, especially in inflation and output
forecasting. It is because any lack of this capability could hinder the smooth implementation
of IT (Debelle, 1997). However, Batini and Laxton (2007) find that this is not a rigor rule.
The start of IT can still work well with some pre-conditions left unfulfilled.
2.1.3 How Does Inflation Targeting Work?
There is no consensus on how inflation targeting should be implemented and the policy
practices also differ from one inflation targeter to the others. But in virtually all cases, central
banks practice what later known as flexible IT. Bernanke and Mishkin (1997) argue that IT
should be considered as a framework and not as a rule. When IT is seen as a framework,
there are spaces for flexibility in which discretionary monetary policy actions can be
accommodated. This implies that IT does not only constrain central banks from making
policy decisions that could lead to undesirable long-run consequences (from its forwardlooking nature), but also permits some discretions when unexpected or exceptional
circumstances occur. Akin to this view, Freedman and Laxton (2009) characterizes a flexible
inflation targeting as a framework that aims at achieving the targeted inflation rate while
minimizing the fluctuations in output and unemployment.
The flexibility of inflation targeting gives chances for short-run stabilization objectives,
especially with respect to output and employment. Bernanke and Mishkin (1997) mention
some ways to achieve short-run stabilization objectives. First, prices that are typically prone
to supply shocks are excluded from the price index on which the official inflation targets are
based. The sources of these prices often are from food and energy prices, indirect tax
changes, terms-of-trade shocks, and the direct effects of interest rate changes on index.
Second, as already mentioned, inflation targets are usually defined as a range and not a single
number. This arrangement gives central some flexibility in the short run to cope with the
uncertainty that lies between policy levers and inflation outcomes. Third, short-term inflation
targets can and have been adjusted to accommodate conditions that could not be controlled
by the central bank, such as supply shocks or other exogenous changes.
Inflation targeting is characterized by the announcement of inflation target, either by the
11
government, central bank, or the combination of both. As previously explained, such target is
usually formed in a range rather than a single point, and is commonly arranged for multiple
horizons ranging from one to four years. Many countries, especially emerging economies,
experienced high rate of inflation before the adoption of IT. Even in some countries like
Poland, Hungary, Serbia, and Ghana the inflation rate were at two digits, reaching around
10%. It was unrealistic for these countries to shrink the inflation rate instantaneously;
therefore, IT generally allowed the transition process from the current level of inflation to the
desired level to occur gradually. In this case, IT in the initial adoption was used as a tool for
price stabilization through a so-called converging-target IT. Converging-target IT means that
the inflation target is set at a moderate and even high inflation levels initially which then
followed by pre-announcing a sequence of descending annual inflation targets to converge
towards stationary targets (Schmidt-Hebbel, 2009). These steady-state targets are usually
consistent with price stability. However, it should be borne in mind that in practice price
stability does not mean zero inflation, but typically around two percent of annual rate of price
change (Bernanke & Mishkin, 1997).
As a way to increase transparency further, inflation-targeting central bank generally publish a
regular, detailed assessment of the policy response. This includes inflation forecasts and
policy responses that are needed to keep inflation on the right path. The Bank of England, for
example, publishes a quarterly Inflation Report that contains detailed economic analyses,
inflation projections as the basis of interest rate decisions, and assessment of the prospects for
the U.K. inflation.
2.1.4 Has InflationTargeting Mattered?
Many benefits can be obtained from introducing IT, which might also explain why the regime
has worked well. Walsh, 2009 points out that the first lesson that could be drawn from IT
experience is that IT is feasible and sustainable. This statement is supported by the fact that
no countries have walked out on IT (Rose, 2007). Albeit its relative new existence among
other monetary regimes, IT has been very durable in producing inflation outcomes (Mihov &
Rose, 2008).
However, there are numerous debates about the successfulness of IT in delivering satisfactory
macroeconomic performance. Stiglitz (2008) argues that inflation targeting will not be able to
12
pass the test in the current economic crisis, while Walsh (2009) contends starkly by stating
that financial crisis or demand shocks in general can be tackled by committing to explicit
inflation target. The ability of IT to enhance macroeconomic performance has been
questioned: whether this has been partially due to sheer good luck of a benign economic
environment or solely to the IT (Lim, 2009, Lin & Ye, 2007, Walsh, 2009, Kurihara, 2010).
This question was raised because the adoption of IT widely occurred during the Great
Moderation, an economic era that was characterized by a low and stable inflation and a
steady economic growth. If the Great Moderation was highly determined by good luck, then
it may be difficult to see the marginal contribution of IT (Walsh, 2009). In general, studies
reveal that the industrialized economies experienced little contribution of IT on either
average inflation rates or inflation volatility, whereas the emerging economies found
significant influence of IT.
In order to see the difference that IT might make, Walsh (2009) suggests to looking at the
three aspects that characterized a monetary policy environment, namely constraints,
objectives, and beliefs. The effect of IT on constraints can be seen from its influence on the
short run tradeoff between inflation and output. First, public will anchor their current and
future expectations based on the explicit announcement of inflation target. This implies that
IT allows a reduction in the average level of inflation without creating any increase in output
volatility. Second, short-run tradeoff between output gap and inflation volatility can be
enhanced by IT. As IT helps to align public’s expectations about future inflation, there will
be greater stability of inflation expectations. This resulted in a lower volatility of inflation
and also of real activity. Third, IT implies greater predictability of current and future targets,
and thereby a decline in the volatility of cost shocks. However, this reduced uncertainty
sometimes is being misinterpreted as good luck.
IT is not only capable in altering the constraints faced by central bank, but also in altering the
objectives of monetary policy. This could be done by clarifying central bank’s objectives and
reassuring the absence of conflict among these objectives, especially with the objective of
achieving and maintaining price stability. However, sometimes this is done with a cost. On
the one hand, IT could indeed promote accountability, but on the other hand IT may sacrifice
other macroeconomic goals (Friedman, 2004). If the latter happens, IT may entail a rise in
real economic volatility.
13
Lastly, public’s beliefs about central bank’s commitment to low inflation could also be
altered by IT. An explicit quantitative target for inflation increases public accountability of
the central bank. Since policy decisions will be more transparent, this increases the incentives
for the central bank to try to meet its target, instead of being distracted by outside pressures
(Koder, Leber, & Mantik, 2010). Furthermore, this induces fewer chances that the central
bank will fall into the time-inconsistency trap. Once a target has been announced, the central
bank will definitely try to meet this target instead of pursuing another policy later, thereby
enables central bank to achieve the gains from an optimal monetary policy. Central banks, for
instance, can thus resist pressures from politicians to undertake expansionary monetary
policy. Although Donald Brash (2000, p.4) argues “No amount of political promises, and no
amount of institutional tinkering, will convince people that low inflation will be an enduring
feature of the economic landscape if what they have actually seen over decades is promises
regularly broken and the value of their money constantly shrinking.”
The way IT influences all these three aspects shows that IT should be associated with a lower
average inflation rate and lower inflation volatility (Walsh, 2009). When IT is able to trim
down uncertainty about policy objectives, anchor public’s expectations about current and
future inflation, and make the central bank’s hands are tied to their commitment, then IT will
also induce a lower volatility of real economic activity. However, in some cases where IT put
too much weight of the policy objectives on inflation, the volatility of real output is likely to
increase.
Several studies have investigated IT from an empirical perspective. Most of the studies
presented in the literature focus on the impact of IT on the behavior of inflation and other
macroeconomic variables, like unemployment, output, and interest rates. Besides, some
studies look at the ability of IT to increase transparency. The results of these studies will be
presented below.
Evidence from industrialized economies
Early study by Freeman and Willis (1995) estimate VAR models for real GDP, price levels,
and interest rates in three IT ancestors, namely New Zealand, Canada, and the U.K. Their
finding shows that interest rates did fall in the early 1990s, which signaled an improvement in
monetary policy credibility. However, this did not persist in the long run. After a few years,
14
long-term rates started to increase again. This may suggest that the credibility effect of IT is
short-lived, although Freeman and Willis argue that a global rise in interest rates may also be
a strong reason for this resurgence. Ammer and Freeman (1995) estimate inflation forecasts
with VAR and compare the results with actual income in the three countries. They find that
inflation fell more than predicted by the VAR in the early 1990s, the time of IT adoption.
However, a study by Debelle (1997) in these countries plus Sweden, Finland, Spain, and
Australia reveals that the decline in inflation rates was followed by an increase in
unemployment in some countries. This indicates that disinflation may occur not without a
cost. Debelle also notes that the benign economic condition in the early 1990s made it
difficult to see this disinflation as a success of IT regime because many non-inflation
targeters also experienced disinflation.
Kahn and Parrish (1998) examine the official central bank interest rate behavior in four IT
countries viz. New Zealand, the U.K., Canada, Sweden and compare it with that in the U.S.
They find that nominal short-term interest rate and its volatility in IT countries have declined
after the adoption of IT. The decline in average short-term official rate was started from 622
basis point in New Zealand and 284 basis point in Sweden. However, the U.S. data also
shows lower volatility of interest rate. The stable economic environment during this period
may give a good reasoning for this result.
Kutner and Posen (1999) estimate VARs for inflation, unemployment, short- and long-term
interest rates to see the impact of IT on these variables. However, their empirical results are
somewhat inconclusive. In Canada and the U.K., the introduction of IT did not lead to a
change in the persistence of inflation, whereas in New Zealand, IT induced a decline in
inflation persistence, but was followed by a stronger reaction to unemployment in the central
bank’s reaction function.
Walsh (2009) compares mean inflation rates and standard deviations between pre- and postIT adoption for ten Organization for Economic and Cooperation Development (OECD)
countries. He finds that the adoption of IT helped to cut down average inflation. In general,
the average decline was about 4.5 percentage points, from 6.55% to 2%. This decline was
associated with a reduction in inflation volatility. In addition, Neumann and Hagen (2002) by
comparing seven inflation targeters with three non-inflation targeters from industrialized
15
countries, also find that IT is not only able to cut down inflation but also to curb the volatility
of inflation and interest rate.
However, the above findings are not enough to justify that IT has succeeded in enhancing
macroeconomic performance. Ball and Sheridan (2005) were the first to discuss that there is
no causal link between IT and better inflation result. They examine twenty OECD countries,
seven are inflation targeters that adopted IT in 1990s and the rest are non-inflation targeters.
Inflation targeters indeed experienced reduced inflation rate, declining inflation volatility,
and stable output growth, but surprisingly, non-inflation targeters also experienced the same
improvements. This evidence shows that all OECD countries, and not only IT countries, have
enjoyed lower and stable inflation rates. Moreover, they also find that non-inflation targeters
obtained lower interest rate volatility than inflation targeters. This evidence makes them
conclude that IT does not improve the economic performance of a country, although they also
note that IT does no harm.
Evidence including developing and emerging market economies
One of the most basic yet important aspects that could indicate whether IT has mattered is the
ability of inflation targeters to keep inflation rate close to their target. Schmidt-Hebbel (2009)
observes inflation deviations from its target for both industrialized economies and emerging
market economies (EMEs). He uses different measures, including mean absolute error, the
mean squared error, and the root mean squared error. As could be seen from Table
2, by large
most inflation targeters have succeeded to meet their target, especially the industrialized
countries. However, some EMEs countries, like Serbia, Brazil, Mexico, Turkey, Indonesia,
and Ghana show rather high deviations from the target.
Another aspect that is of importance to be observed is transparency. Chortareas, Stasagave,
and Sterne (2000) compare monetary policy transparency across 87 countries and find that
transparency is a significant determinant of inflation rates and it affects inflation rates
negatively. Since IT enhances the transparency of monetary policy, this result supports the
view that IT is associated with a decline in inflation level. Svensson (1997) dubs IT as
“inflation-forecast” targeting because the ability of IT to increase transparency is highly
affected by inflation forecasts. Inflation forecasts could enhance and reinforce transparency
and governance though better communication of policy decisions and macroeconomic
16
analysis to the public (Eijffinger & Geraats, 2006, Geraats, 2008). In turn, increased
transparency will bring about higher credibility.
In addition, Dincer and Eichengreen (2007) observe that the most transparent central banks
appear to be inflation targeters, which are New Zealand, Sweden, the U.K, Canada, and the
Czech Republic. Moreover, by investigating trends in transparency across four different
monetary policy regimes over the period 1998-2006, Geraats (2008) finds that IT countries
achieve by far the highest level of aggregate central transparency, which can be seen in
Figure
1. More specifically, Figure
2 depicts the enhancement in transparency experienced by
industrialized countries and emerging market economies during 1998-2005. Industrialized
economies experienced much higher index of transparency than emerging market economies,
but the gap has been shrinking over time.
Some central banks in the EMEs have done individual study to see the effect of IT on their
economies and find that the credibility of monetary policy and inflation targets has increased.
This is particularly seen in Chile, the Czech Republic, Mexico, and Colombia. In general,
these countries experienced more anchored expectations following an improvement of
credibility. In Colombia, this enhanced credibility has partly contributed to a reduction in
inflation persistence. Capistrán and Ramos-Francia (2007) explain that a credible inflation
target will make agents set prices and wages based on this target, and thus weakening
indexation mechanisms and adaptive expectations. As a result, shocks do not have permanent
effects on inflation. In addition, central banks will also require less aggressive policy
adjustments (Moreno, 2008).
Evidence on inflation expectations
Many of the potential benefits from IT work through its effect in anchoring expectations of
future inflation. Walsh (2009) describes three ways to gauge the effects of IT on inflation
expectations. First is by seeing how the inflation expectations react to news. Using inflation
expectations implied by bond yields, Gürkaynak, Levin, & Swanson (2006) find a significant
anchoring effect of inflation targeting. They test the responsiveness of inflation expectations
to economic news and find that the inflation expectations in the U.S. reacted to news; an
evidence that is not found in Sweden, an inflation targeter. This finding suggests that the
expectations in Sweden were firmly anchored. This finding is confirmed by Gürkaynak,
17
Levin, Marder, & Swanson (2007).
The second way to see the impact of IT on inflation is by observing whether the lag in
inflation is correlated with the expectations of future inflation. Levin, Natalucci, and Piger
(2004) estimate the effects of lagged inflation on long-term inflation expectations for several
IT and non-IT industrialized countries. They find that lagged inflation is significantly
correlated with expectations of future inflation in the non-IT countries. This correlation is
non-existence among IT countries and thus shows that IT does play a role in anchoring
inflation expectations.
Lastly, it could also be measured by looking at the distribution of inflation expectations.
Carrera (2008) uses this approach to see how well IT in anchoring expectations in Peru. He
observes the distribution of individual responses to a survey of inflation expectations in this
country from 2000 to 2007. The finding shows that since the adoption of IT in 2002, the
distribution of inflation expectations has been shifting significantly. Almost all the mass of
the distribution was concentrated within the official target ranges.
2.2 Interest Rate Channel
2.2.1 The Importance of Interest Rate Channel
A good understanding of monetary transmission mechanism is one of the keystones of
modern monetary policymaking (Gigineishvili, 2011). Monetary transmission mechanism is a
process through which changes in central bank policy are transmitted to the real sector,
allowing the central bank to steer the economy to attain the designated objectives. This
mechanism consists of four main channels, namely the exchange rate channel, the interest
rate channel, the asset prices channel, and the credit channel (Mishkin, 1996). The
effectiveness of monetary policy relies on the speed and the strength of each of these
channels. All these four channels transmit policy actions to aggregate demand through
financial markets. However, the type of financial market that is used as a medium of pass
through differs from one channel to the other channels (Gigineishvili, 2011).
The interest rate channel works when a change in the policy rate is transmitted immediately
to the short-term wholesale money markets, such as repos and interbank deposits. The
18
adjustment of long-term interest rate, however, occurs gradually and more complex. Interest
rate channel emphasizes on the impact of real interest (rather than nominal) on consumer and
business decisions due to its importance in affecting spending (Mishkin, 2009). With the
sticky prices notion, in which the aggregate price level adjusts only gradually over time, an
expansionary monetary policy does not only lower the short-term nominal interest rates but
also the short-term real interest rates. The expectation hypothesis of term structure postulates
that the long-term interest rate is determined by the average of expected future short-term
interest rate; therefore, a persistent change in short-term real interest rate eventually reflects a
change in long-term real interest rate (Bank of England, 2005, ECB, 2000, Kusmiarso,et al.,
2002, Loayza & Schmidt-Hebbel, 2002, Mishkin, 2009). Changes in market interest rates will
alter lending and deposit rates, which then influence investment and saving decisions made
by firms and households. Eventually, this will affect aggregate demand and inflation.
The asset price channel basically works in a similar way with the interest rate channel, but
through the market value of securities, such as bonds, stocks, and equities. The policyinduced changes in interest rates alter the prices of these assets, which then influence the
effective cost of capital and the net worth of households and firms. Consumption and
investment will be adjusted accordingly, and as a result, aggregate demand and prices will
also be affected.
The policy-induced changes in interest rates can also affect the exchange rate through foreign
exchange market. The exchange rate represents the relative price between domestic and
foreign money. An unexpected increase (decrease) in policy rate, ceteris paribus, quickly
reflects in an appreciation (depreciation) of the domestic currency. The appreciation
(depreciation) of the exchange rate implies a higher (lower) domestic interest rate relative to
foreign-currency assets, making domestic assets more (less) attractive to international
investors. The higher (lower) value of the domestic currency is reflected in a higher (lower)
price of domestic goods relative to foreign goods, causing a decrease (increase) in net export
and consequently a decrease (increase) in aggregate demand.
Lastly, the credit channel operates through the effects of asymmetric information problems in
financial market on bank lending and firms’ and households’ balance sheet. Asymmetric
information problems in financial market are the moral hazard and the adverse selection
problems. An expansionary monetary policy, for example, raises the price of stock and
19
increases the net worth of firms, and thus driving down moral hazard and adverse selection
problems. As a result, investment spending increases which will be followed by a rise in
aggregate demand.
The exchange rate channel is believed to play a vital role at the early stages of financial
development (Gigineishvili, 2011). It is because foreign exchange is seen as the sole most
liquid and inflation proof asset in countries with undeveloped capital and money markets.
This view is supported by the evidence that exchange rate pass-through is much stronger in
emerging market economies than in industrialized economies (Korhonena & Wachtel, 2005,
Tieman, 2004). The other three channels generally perform well in more developed markets
(Gigineishvili, 2011). Credit channel is of significance in markets with limited
substitutability. Interest rate channel and asset price channel appear to be weak when the
financial system is shallow and poorly diversified (Loayza & Schmidt-Hebbel, 2002). In
countries with high inflation, the interest rate channel is also weak because high inflation
usually entails high volatility of inflation (Lopes, 1998).
Recently, there is a worldwide emergence of using short-term interest rate as the main
instrument of monetary signals, which makes the interest rate channel as the key transmission
channel. In addition, interest rate channel is one of the main foundations in IT regime, a
regime that has been adopted by a growing number of countries. In emerging countries, the
interest rate channel was weak during the 1980s and 1990s. This could occur because, inter
alia, the bond and money markets were not well developed and there were frequent shifts in
the risk premium. However, evidences show that the role of interest rate channel in emerging
countries has increased through time (Mohanty & Turner, 2008). In Thailand, interest rate
channel has become more important after the countries hit by the 1997-98 crises. In the
Philippines, central bank lending rate dominates the transmission channel in the long run. In
Czech Republic and Poland, there has been an increase in pass-through from policy rates to
deposit and lending rates. In Mexico, the role of exchange rate has fallen quite significantly
in early 2000 and as a return, interest rate started to contribute more to the short- and longrun variation in output and inflation. All in all, more and more emerging market economies
follow the operating systems of monetary policy in industrialized economies, i.e. the central
bank sets a short-term interest rate (policy rate) and market will determine other interest rates
in the economy.
20
As interest rate channel has become increasingly important, there have been extensive
empirical researches that seek to measure the qualitative and quantitative properties of
interest rate pass-through. This pass-through shows the movement of changes in policy rate
to changes in the target variables. Interest rate pass-through could be divided into three
phases. First, changes in policy rates leads to changes in market rates, from the short-term
rates moving to the long-term rates. Second, changes in market rates are transmitted further
to commercial bank lending and deposit rates. Finally, these changes influence savings,
investments, and consumptions, which altogether determine the level of aggregate demand
and prices. The first phase generally occurs strongly and quite immediate. The second phase
is more divergent and is an important phase in the process of monetary transmission. As the
pass-through from market interest rates to loan and deposit rates gets quicker and fuller,
monetary policy transmission will be stronger (Bondt, 2002). It is therefore important to
understand the degree and speed at which changes in policy rates are passed-through to retail
rates faced by firms and households. A complete pass-through happens when there is a one
for one change from money market rates to retail rates. The retail rates are considered to be
sticky when they respond sluggishly to movements in the money market.
2.2.2 Determinant of Interest Rate Pass-Through
As already mentioned, the strength and speed of interest rate pass-through contribute to the
effectiveness of monetary policy transmission mechanism. Moreover, in liberalized financial
environment, the responsiveness of loan and deposit rates acts as a key feature of the
monetary transmission process (Kamin, Turner, & Van‘t dack, 1998). A stronger and more
rapid response of interest rates faced by borrowers and lenders to changes in money market
rates makes the transmission of policy rate to the real economy becomes more effective.
There are several factors that determine the strength and speed of interest-rate pass through.
The most important factor is the competitiveness, depth, and diversity of the financial market.
The degree of competition plays a key role in determining the speed and strength of the
responsiveness of the loan and deposit rates (Kamin, Turner, & Van‘t dack, 1998). In an
environment where there are numerous banking institutions and competitive market
conditions, changes in the cost of fund will immediately reflect in the loan and deposit rates.
Leuvensteijn, Sørensen, Bikker, and Rixtel (2008) investigate some countries in the euro area
and also find that a stronger competition in the market of these countries resulted in a faster
21
transmission process. Moreover, a highly competitive banking market combined with
improved availability of alternative capital market-based instrument for financial instrument
will speed up the pass-through further (Gropp, Sørensen, & Lichtenberger, 2007). In a
contrast, a banking sector that is highly concentrated will make the response of loan and
deposit rates sluggish and asymmetric. The responsiveness of loan and deposit rate also tends
to be weaker when state-owned banks are present because these banks are not forced to
maximize profits.
Kamin, Turner, & Van‘t dack (1998) argue that as the financial market gets deeper, the role
of expectations will be enhanced. Consequently, this will hasten the speed at which changes
in short-term rates are passed-through to other interest rates. Additionally, they also note that
a thin or uncompetitive financial market can increase the volatility of money market interest
rates. If the money market interest rates are highly volatile and tend to reverse their
movements quickly, banks will be reluctant to adjust the loan and deposit rates because it
entails high cost. As a consequence, interest rate pass through loses its strength.
Weber, Gerke, and Worms (2009) mention that financial innovation can shorter the link
between short-term market rates and lending rates. Based on their study, Gropp, Sørensen,
and Lichtenberger (2007) find that advances in risk management technologies is one of the
factors that could speed up the pass-through. Their results show that a high pass-through from
long-term rates to rates on mortgages could be obtained when the access to financial
instruments is easy. In addition, Kamin, Turner, and Van‘t dack (1998) mention that the
access of household and firms to alternative domestic funding sources, such as securities
markets also determines the loan and deposit rates set by the domestic banking system. The
more various the alternative funding sources, the faster the speed of pass through. Moreover,
if there is a good integration between the banking sector and the securities markets, then
banks will be more pressured to improve interest rates responsiveness under their control.
Volatility in money markets is another factor that determines the speed and strength of
interest rate pass-through. Higher volatility tends to weaken the pass-through (Gigineishvili,
2011, Cottarelli and Kourelis, 1994, Mojon, 2000, and Sander and Kleimeier, 2004).
Gigineishvili (2011) explains that the money market interest rates carry reliable information
that is needed for banks to alter the deposit and loan rates. High volatility in the money
markets brings about uncertainty into market signals, making banks be more cautious in
22
passing market rates to their customers. They prefer to wait until the noise is no longer there.
In line with this, Lopes (1998) argue that in the case of high inflation, the high volatility of
inflation should be taken into consideration when determining real interest rates. It means
that the relevant cost of capital concept will be equal to nominal interest rates minus the
certainty equivalent of inflation. This certainty equivalent will exceed its expected value by a
‘volatility’ premium when inflation is highly volatile; therefore, in the economy with high
inflation volatility, a high real interest rate is not always similar to a monetary tightening. In
addition, Lopes also notes that as the stabilization policies have been able to reduce inflation
volatility, the interest rate channel will be stronger.
Statistical evidence shows that bank rates responsiveness to a change in policy rate has been
slower in emerging market economies than in industrialized economies (Kamin, Turner, &
Van‘t dack, 1998). Low competition, less flexibility, and limited depth of financial markets in
the emerging countries might be the reason for this result. It is therefore needed to develop
the financial markets in these countries to strengthen transmission. Gigineishvili (2011)
argues that countries with underdeveloped financial markets should opt for a monetary
framework that uses monetary aggregates or exchange rates as a nominal anchor rather than
inflation targeting framework that depends heavily on strong interest rate pass-through.
2.2.3 Evidence on Interest Rate Pass-Through
As already mentioned, the strength and speed of interest rate pass-through contribute to the
effectiveness of monetary policy transmission mechanism. Moreover, in liberalized financial
environment, the responsiveness of loan and deposit rates acts as a key feature of the
monetary transmission process (Kamin, Turner, & Van‘t dack, 1998). A stronger and more
rapid response of interest rates faced by borrowers and lenders to changes in money market
rates makes the transmission of policy rate to the real economy becomes more effective.
There are several factors that determine the strength and speed of interest-rate pass through.
The most important factor is the competitiveness, depth, and diversity of the financial market.
The degree of competition plays a key role in determining the speed and strength of the passthrough to loan and deposit rates (Kamin, Turner, & Van‘t dack, 1998). In an environment
where there are numerous banking institutions and competitive market conditions, changes in
23
the cost of fund will immediately reflect in the loan and deposit rates. Leuvensteijn,
Sørensen, Bikker, and Rixtel (2008) investigate some countries in the euro area and also find
that a stronger competition in the market of these countries resulted in a faster transmission
process. Moreover, a highly competitive banking market combined with improved
availability of alternative capital market-based instrument for financial instrument will speed
up the pass-through further (Gropp, Sørensen, & Lichtenberger, 2007). In a contrast, as
already mentioned, a banking sector that is highly concentrated will make the response of
loan and deposit rates sluggish and asymmetric. The responsiveness of loan and deposit rate
also tends to be weaker when state-owned banks are present because these banks are not
forced to maximize profits.
The adjustment of deposit and lending rates, however, sometimes appears to be asymmetric.
In Colombia, pass through to deposit rates was quicker than to loan rates due to greater
competition in the deposit market than in the loan market. The same case also occurred in
Indonesia and Thailand. Commercial banks in these countries were likely to adjust the
deposit rates more frequently than the loan rates. In general, the adjustment of deposit and
loan rates in the banking sector depends on the initiative of the most prominent banks in the
deposit and loan segment of the market (Kamin, Turner, & Van‘t dack, 1998).
Statistical evidence shows that bank rates responsiveness to a change in policy rate has been
slower in emerging market economies than in industrialized economies (Kamin, Turner, &
Van‘t dack, 1998). Low competition, less flexibility, and limited depth of financial markets in
the emerging countries might be the reason for this result. It is therefore needed to develop
the financial markets in these countries to strengthen transmission. Gigineishvili (2011)
argues that countries with underdeveloped financial markets should opt for a monetary
framework that uses monetary aggregates or exchange rates as a nominal anchor rather than
opt for inflation targeting framework that depends heavily on strong interest rate passthrough.
24
Chapter 3
MONETARY POLICY IN INDONESIA
This chapter aims to give a brief overview of the conduct of monetary policy in Indonesia,
emphasizing on the background of the adoption of IT framework. Besides, this chapter also
provides a short explanation about how the interest rate channel works in Indonesia and how
well this channel performed during the pre- and post-crisis period.
3.1 The Adoption of Inflation Targeting
Since 1970, Indonesia has opted for three different exchange rate regimes. A fixed exchange
rate regime was implemented from 1970 to 1978 and a managed floating exchange rate was
chosen thereafter. However, due to a strong pressure on the rupiah at the onset of the 1997
crisis, the managed floating regime had to be abandoned. In August 1997, the rupiah started
to free float. This new regime implies that the value of rupiah as an exchange rate is strongly
determined by the supply and demand in the market.
The crisis in 1997 brought a severe impact to the Indonesian economy and was considered to
be the worst recession the economy has experienced (Goeltom, 2008). The output shrank by
13.68% and annual inflation rate skyrocketed to 77.6% in 1998 (year on year basis). Capital
flight and unfavorable market sentiment were rampant, worsening the economy as they
entailed excessive exchange rate volatility. It then became increasingly difficult for monetary
policy to maintain the stability of rupiah. Moreover, as the weakening rupiah passed-through
its effect to inflation, the interest rate had to be raised sharply to support economic and
financial stability. The high interest rate combined with the substantial depreciation of the
rupiah have worsened the banks’ asset quality and partly induced corporate failures. To
prevent the collapse of the entire banking system, Bank Indonesia had to provide liquidity
support to commercial banks, and thus raising the base money. This vicious cycle was likely
to worsen the economic further and trigger hyperinflation. Before that happened, BI decided
to stabilize the economy by restoring confidence in the national currency.
During this stabilization period, BI gained support from the IMF. The IMF advised BI to
tighten the monetary policy and adopt base money as both the operational target and the
nominal anchor, but still kept its eye on various aggregates and interest rates. However, along
25
the time the use of base money as the operating target was found to be ineffective.
Policymakers argued that it was troublesome to control M0 growth, making it difficult to
achieve the base money target (Goeltom, 2008, Warjiyo & Agung, 2002). Moreover, base
money could not give a good signal to the market, and thereby failed to maintain market
expectations on future exchange rate movements.
Following the abandonment of the managed floating exchange rate and the failing of base
money as a nominal anchor, BI needed to choose an alternative nominal anchor. With this
background, BI decided to choose inflation as a nominal anchor. As argued by Freedman and
Laxton (2009), a nominal anchor is a vital element for conducting monetary policy because it
helps to give clarity about the (intermediate and final) objectives of the central bank, and thus
abating the central bank to achieve these objectives. By using inflation as the nominal anchor,
public will be well guided to shape their inflation expectations needed to make decisions on
investments and savings. Beside the need to find an alternative nominal anchor, BI’s decision
to shift to IT regime was because there have been an increasingly number of countries joined
the IT club and gained success in lowering inflation rate while keeping output volatility at a
low level (Alamsyah, Joseph, Agung, & Zulverdy, 2001).
In 1999, a new central bank act was enacted, namely the Act No. 23/1999. This act was then
revised into the Act No. 3/2004. This new act postulates that BI is obliged to announce
inflation target at the beginning of the year, starting from 2000. Besides, this act also
mandates BI to (1) set price stability as the ultimate objective, (2) be independent in both
setting the inflation target (goal independence) and conducting the monetary policy
(instrument independence), (3) be free from governments’ and other parties’ intervention
when choosing monetary policy, (4) have a clear mechanisms that strengthen its
accountability and transparency in implementing policies (Goeltom, 2008). These core points
of the act suit the characteristics of a central bank adopting IT framework as asserted by
(Bernanke, Laubach, Mishkin, & Posen, 1999). The declaration of this act became the basis
for central bank independence needed for the implementation of IT framework in the future.
As mandated by the new act, BI has announced the annual inflation target and the plan of
monetary policy since the beginning of 2000. However, it is worth noting that during this
period, the explicit announcement of inflation target does not imply that BI has already
adopted an IT framework. As what explained by (Stone, 2003), during this period BI could
26
be considered to perform a “lighter” version of IT as a preparation towards a full-fledged IT.
The official adoption of a full-fledged IT framework in Indonesia occurred later in July 2005.
In implementing IT, BI follows a flexible-type of IT which implies that IT is seen as a
framework and not a rigor rule. With this principle, when performing monetary policy, BI
also takes into account other goals other than a low and stable inflation.
Since the enactment of Act no. 23/1999, BI has made a number of serious efforts to enhance
the quality and credibility of its monetary policy (Goeltom, 2008, Warjiyo & Agung, 2002).
These were done as preparations towards the implementation of IT as well as to support BI’s
role for nurturing the economic recovery in Indonesia. To monitor the monetary policy stance
and direction, BI conducts a monthly Board of Governors meeting. In addition, BI also
carries extensive researches to provide better analysis and forecasts of inflation, economic,
financial trends, and policy scenarios for the monetary policy, which was of importance to
support BI in making decision. The announcement of inflation target and the consistent
achievement of this target will raise the credibility of the monetary policy taken by BI.
Increased credibility will make public expectations ally with the target set by BI.
To increase transparency, BI communicates the result of the Board of Governors meeting to
the public through various media, including press releases, press conferences, seminars with
academicians and other stakeholders, as well as on the Bank’s website. BI also provides
quarterly reports to the Parliament to increase accountability. These reports include a review
of monetary policy and other tasks of BI on banking and payment system. All these efforts
done by BI since the beginning of 2000 are important to speed up the adoption of a fullfledged IT framework.
IT is forward-looking in the sense that BI needs to respond to future developments of
inflation. At the operational level, BI rate as the policy rate is used to respond to the future
trend of inflation. BI rate is announced by the Board of Governors of BI in each monthly
Board of Governors meeting. The BI rate is implemented through open market operations for
one-month Sertifikat Bank Indonesia (SBI) or BI’s certificates. SBI is used because of three
important reasons, which are (1) it is a good signaling tool of monetary policy response, (2) it
is used as benchmark by banks and market players in Indonesia, (3) it plays a prominent role
in monetary transmission mechanism (Goeltom, 2008). When the forecasted future inflation
27
lies above (below) the established inflation target, BI generally will raise (lower) the BI rate.
This is done without neglecting other factors in the economy.
To achieve the monetary policy operational target, the BI monetary operations are used as a
medium where BI rate is adjusted based on the liquidity management on the money market.
The monetary policy operational target will determine the movement of the interbank
overnight (O/N) rate. Changes in interbank O/N rate will be followed by changes in the
deposit and lending rates. These changes will eventually affect output and inflation.
3.2 Interest rate channel
In Indonesia, the BI rate serves as the main instrument for influencing economic activity and
the overriding objective of attaining the chosen inflation target; hence, BI rate adjustments
become the starting point of the monetary transmission mechanism. The transmission of BI
rate decisions to achieve the targeted inflation level operates through five different channels
and subject to time lag. These channels are the interest rate channel, the exchange rate
channel, the asset price channel, the credit channel, and the expectations channel.
There have been an extensive number of literatures that study the various transmission
channels and how well they affect the effectiveness of monetary policy. Some recent studies
allow for financial market imperfections, and it is found that financial market imperfections
add the complexity of the monetary transmission mechanism. Imperfections and asymmetric
information in financial markets may affect the transmission channels. Warjiyo & Agung,
(2002) argue that the relative strength of the five transmission channels in general depends on
the existing structure and arrangements of a country’s economy and financial markets. Due to
this reason, monetary transmission is often dubbed as a “black box” in the theory of monetary
policy.
Understanding monetary transmission mechanism is of importance for Indonesia in order to
enhance the role of monetary policy in maintaining the stability of the rupiah as a way to
foster economic recovery during the crisis period (Warjiyo & Agung, Monetary Transmission
in Indonesia: An Overview, 2002). As the crisis went by and Indonesia decided to adopt IT
framework in 2005, the smooth functioning of monetary transmission mechanism gained
importance to support the successfulness of IT adoption and implementation in Indonesia. It
28
is because the effectiveness of monetary policy is determined by how well the transmission
channels transmit changes in the BI rate to the real economy and prices. With this
background, BI conducted comprehensive researches in 2001 to study the transmission
mechanisms through the five different channels of monetary policy. The results of these
studies, more specifically on the interest rate channel, will be discussed further here.
The interest rate channel in Indonesia transmits changes in the BI rate to bank deposit and
lending rates. When the economy experiences a downturn, BI should stimulus the economy
by lowering the interest rates. The decrease in interest rates will be followed by a reduction in
bank lending rates. As the loan rates decline, corporate and household demand for credit will
be enhanced. In addition, this will also reduce the cost of capital for companies engaging in
investment. As a result, investment and consumption increases which in turn will boost the
economy. On the other hand, when the inflationary pressure increases, BI will raise the BI
rate to reduce the inflationary pressure and slow down the economic activity.
The study about the strength of interest rate channel in Indonesia was done by Kusmiarso, et
al.(2002). Using VAR analysis and Granger test, they investigate the relationship between the
policy rate and real sector variables. They also observe the behavior of banking markets in
responding to policy rate, involving several micro factors on banks, namely the interbank
O/N rate, deposit rate, and credit rate. The study emphasizes the observation on the period
before and after the 1997 crisis.
Before the crisis, empirical evidence from VAR analysis shows that the interbank rate was
the main determinant of real deposit rate and real investment credit rate. However, real credit
rate did not strongly influence investment growth. Investment growth, instead, appeared to
rely heavily on the high access to foreign borrowing. The same case also occurred with
consumption growth as it was weakly affected by changes in real deposit rate. This could
happen due to the stable and relatively low real deposit rate. Study also reveals that changes
in the policy rate were transmitted to the loan rate within a faster period than to the deposit
rate. It took three months for the loan rate and six months for the deposit rate. This behavior
was plausible since deposit rate represent banks’ cost while the loan rate represents banks’
revenue. During this period, the investment loan rates were responsive to a change in the
interbank rate due to the boom in the economy and the high need for fund from the business
sector.
29
For the post-crisis period, the real deposit rate and real investment credit rate were less
responsive to the interbank rate than the pre-crisis period. An increase in the interbank rate
did have an influence on the one-month deposit real interest rate, but with a smaller
magnitude that the three-month deposit real interest rate. In the mean time, the increase of
interbank rate initially resulted in a negative growth of consumption for the same period. The
real investment credit rate, however, did not adjust with the same magnitude as the change in
the deposit rate. This occurred because generally agents in the money market are more
sensitive to higher loan rate than higher deposit rate. A higher loan rate will likely to induce
higher debtor fault and non-performing loan, and thus increasing the risks of the banks in
lending money. However, unlike the pre-crisis period, this period showed that the investment
(consumption) growth has been strongly affected by the real investment credit rate (real
deposit rate).
30
Bibliography
Alamsyah,
H.,
Joseph,
C.,
Agung,
J.,
&
Zulverdy,
D.
(2001).
Towards
Implementation
of
Inflation
Targeting
in
Indonesia.
Bulletin
of
Indonesian
Economic
Studies,
309‐324.
Ammer,
J.,
&
Freeman,
R.
T.
(1995).
Inflation
targeting
in
the
1990s:
The
experiences
of
New
Zealand,
Canada,
and
the
United
Kingdom.
Journal
of
Economics
and
Business,
165‐192.
Ball,
L.,
&
Sheridan,
N.
(2005).
Does
Inflation
Targeting
Matter?
In
B.
S.
Bernanke,
&
M.
Woodford,
The
Inflation
Targeting
Debate.
Chicago:
The
University
of
Chicago
Press.
Bank
of
England.
(2005).
The
Transmission
Mechanism
of
Monetary
Policy.
Retrieved
December
2012,
from
Bank
of
England:
www.bankofengland.co.uk
Batini,
N.,
&
Laxton,
D.
M.
(2007).
Under
What
Conditions
Can
Inflation
Targeting
Be
Adopted?
The
Experience
From
Emerging
Markets.
Central
Bank
of
Chile,
467‐506.
Bernanke,
B.
S.,
&
Mishkin,
F.
S.
(1997).
Inflation
Targeting:
A
New
Framework
for
Monetary
Policy?
Journal
of
Economic
Perspectives,
97‐116.
Bernanke,
B.
S.,
Laubach,
T.,
Mishkin,
F.
S.,
&
Posen,
A.
S.
(1999).
Inflation
Targeting
Lessons
from
the
International
Experience.
New
Jersey:
Princeton
University
Press.
BI.
(n.d.).
Monetary.
Retrieved
December
2011,
from
Bank
Indonesia:
http://www.bi.go.id/web/en/Moneter/
Boediono.
(1998).
Merenungkan
Kembali
Mekanisme
Transmisi
Moneter
di
Indonesia
(Revisiting
Monetary
Transmission
Mechanism
in
Indonesia).
Buletin
Ekonomi
Moneter
dan
Perbankan
Vol.
1,
No.
1,
1‐4.
Bondt,
G.
D.
(2002).
Retail
Bank
Interest
Rate
Pass‐Through:
New
Evidence
at
the
Euro
Level.
European
Central
Bank,
Working
Paper
No.
136.
.
Brash,
D.
T.
(2000,
February
9).
Inflation
Targeting
in
New
Zealand,
1988­2000.
Retrieved
February
2012,
from
Reserve
Bank
of
New
Zealand:
http://www.rbnz.govt.nz/speeches/0086932.html
Capistrán,
C.,
&
Ramos‐Francia,
M.
(2007).
Does
Inflation
Targeting
Affect
the
Dispersion
of
Inflation
Expectations?
Documento
de
Investigación
2007–11,
Dirección
General
de
Investigación
Económica,
Banco
de
México.
Carrera,
C.
(2008).
Rational
Expectations
and
Credibility:
The
Case
of
Peru
.
Chortareas,
G.,
Stasagave,
D.,
&
Sterne,
G.
(2000).
Does
it
Pay
to
be
Transparent?
International
Evidence
from
Central
Bank
Forecasts.
Bank
of
England.
Cottarelli,
C.,
&
Kourelis,
A.
(1994).
Financial
Structure,
Bank
Lending
Rates
and
the
Transmission
Mechanism
of
Monetary
Policy.
IMF
Working
Paper.
Debelle.
(1997).
Inflation
Targeting
in
Practice.
IMF
Working
Papers.
Dincer,
N.
N.,
&
Eichengreen,
B.
(2007).
Central
Bank
Transparency:
Where,
Why,
and
with
What
Effects?
NBER
Working
Paper
.
ECB
.
(2000,
June).
Monetary
Policy
Transmission
in
the
Euro
Area.
ECB
Monthly
Bulletin,
pp.
43‐58.
Eijffinger,
S.
C.,
&
Geraats,
P.
M.
(2006).
How
transparent
are
central
banks?
European
Journal
of
Political
Economy,
1‐22.
Freedman,
C.,
&
Laxton,
D.
(2009).
Why
Inflation
Targeting?
IMF
Working
Paper.
Freeman,
R.
T.,
&
Willis,
J.
L.
(1995).
Targeting
Inflation
in
the
1990s:
Recent
Challenges.
International
Finance
Discussion
Papers.
31
Friedman,
B.
M.
(2004).
Why
the
Federal
Reserve
Should
Not
Adopt
Inflation
Targeting.
International
Finance,
129‐136.
Geraats,
P.
M.
(2008).
Trends
in
monetary
policy
transparency.
Bank
of
Canada
Economic
Conference
Presentation.
Ottawa.
Gigineishvili,
N.
(2011).
Determinants
of
Interest
Rate
Pass‐Through:
Do
Macroeconomic
Conditions
and
Financial
Market
Structure
Matter?
IMF
Working
Paper.
Goeltom,
M.
(2008).
The
Transmission
Mechanisms
of
Monetary
Policy
in
Indonesia.
BIS
Papers
No.
35,
317‐340.
Gropp,
R.,
Sørensen,
C.
K.,
&
Lichtenberger,
J.
(2007).
The
Dynamics
of
Bank
Spreads
and
and
Financial
Structure.
ECB
Working
Papers.
Gürkaynak,
R.
S.,
Levin,
A.
T.,
&
Swanson,
E.
T.
(2006).
Does
Inflation
Targeting
Anchor
Long‐Run
Inflation
Expectations?
Evidence
from
Long‐Term
Bond
Yields
in
the
U.S.,
U.K.,
and
Sweden.
Working
Paper
Series
2006­2009,
Federal
Reserves
of
San
Fransisco.
Gürkaynak,
R.
S.,
Levin,
A.
T.,
Marder,
A.
N.,
&
Swanson,
E.
T.
(2007).
Inflation
Targeting
and
the
Anchoring
of
Inflation
Expectations
in
The
Western
Hemisphere.
In
F.
S.
Mishkin,
&
K.
and
Schmidt‐Hebbel,
Monetary
Policy
under
Inflation
Targeting.
Banco
Central
de
Chile.
Hammond,
G.
(2010).
State
of
the
Art
of
Inflation
Targeting.
Centre
for
Central
Bank
Studies,
Handbook
­
No.
29,
Bank
of
England.
Kahn,
G.
A.,
&
Parrish,
K.
(1998).
Conducting
Monetary
Policy
with
Inflation
Targets.
Federal
Reserve
Bank
of
Kansas
City
Economic
Review,
5‐32.
Kamin,
S.,
Turner,
P.,
&
Van
‘t
dack,
J.
(1998).
The
Transmission
Mechanism
of
Monetary
Policy
in
Emerging
Market
Economies:
An
Overview.
BIS
policy
papers
no.3,
8‐67.
Kamin,
S.,
Turner,
P.,
&
Van‘t
dack,
J.
(1998).
The
Transmission
Mechanism
of
Monetary
Policy
in
Emerging
Market
Economies:
An
Overview.
BIS
policy
papers
no.3,
8‐67.
Koder,
S.,
Leber,
A.,
&
Mantik,
W.
(2010).
Has
Inflation
Targeting
Prove
a
Success
in
Industrialized
Countries?
Universiteit
Van
Amsterdam.
Korhonena,
I.,
&
Wachtel,
P.
(2005).
A
note
on
exchange
rate
pass‐through
in
CIS
countries.
Research
in
International
Business
and
Finance.
Kurihara,
Y.
(2010).
Has
Inflation
Targeting
Been
Effective?
International
Journal
of
Business.
Kusmiarso,
B.,
Sukawati,
E.,
Pambudi,
S.,
Angkoro,
D.,
Prasmuko,
A.,
&
Hafidz,
I.
S.
(2002).
Interest
Rate
Channel
of
Monetary
Transmission
in
Indonesia.
In
P.
Warjiyo,
&
J.
Agung,
Transmission
Mechanisms
of
Monetary
Policy
in
Indonesia
(pp.
33‐108).
Jakarta:
Bank
Indonesia.
Kutner,
K.
N.,
&
Posen,
A.
S.
(1999).
Does
Talk
Matter
After
All?
Inflation
Targeting
and
Central
Bank
Behavior.
Federal
Reserve
Bank
of
New
York
Staff
Report.
Leuvensteijn,
M.
v.,
Sørensen,
C.
K.,
Bikker,
J.
A.,
&
Rixtel,
A.
A.
(2008).
Impact
of
Bank
Competition
on
the
Interest
Rate
Pass‐Through
in
the
Euro
Area.
Tjalling
C
Koopmans
Research
Institute,
Discussion
Paper
Series.
Levin,
A.
T.,
Natalucci,
F.
M.,
&
Piger,
J.
M.
(2004).
The
Macroeconomic
Effects
of
Inflation
Targeting.
Federal
Reserve
Bank
of
St.
Louis,
51‐80.
Lim,
G.
C.
(2009).
Inflation
Targeting.
The
Australian
Economic
Review,
110‐118.
Lin,
S.,
&
Ye,
H.
(2007).
Does
Inflation
Targeting
Really
Make
a
Difference?
Evaluating
the
Treatment
Effect
of
Inflation
Targeting
in
Seven
Industrial
Countries.
Journal
of
Monetary
Economics,
21‐33.
32
Loayza,
N.,
&
Schmidt‐Hebbel,
K.
(2002).
Monetary
Policy
Functions
and
Transmission
Mechanism:
An
Overview.
Retrieved
December
2011,
from
Banca
Central:
http://www.bcentral.cl/Estudios/banca‐central/pdf/v4/001_020Gallego.pdf
Lopes,
F.
L.
(1998).
The
Transmission
Mechanism
of
Monetary
Policy
in
a
Stabilizing
Economy:
Notes
on
the
Case
of
Brazil.
In
The
Transmission
of
Monetary
Policy
in
Emerging
Market
Economies
(pp.
65‐
72).
BIS
Policy
Papers
No.
3.
Mihov,
I.,
&
Rose,
A.
K.
(2008,
April
24).
Is
Old
Money
Better
Than
New?
Duration
and
Monetary
Regimes.
Retrieved
February
2012,
from
Economics:
The
Open‐Access,
Open‐Assessment
E‐Journal:
http://www.economics‐ejournal.org/economics/journalarticles/2008‐13.
Mishkin,
F.
S.
(1996).
Understanding
Financial
Crises:
A
Developing
Country
Perspective.
In
M.
Bruno,
&
B.
Pleskovic,
Annual
World
Bank
Conference
on
Development
Economics
1996
(pp.
29‐62).
Washington
D.C:
World
Bank.
Mishkin,
F.
S.
(2000).
Inflation
Targeting
in
Emerging
Market
Countries.
NBER
Working
Paper
Series.
Mishkin,
F.
S.
(2009).
The
economics
of
Money,
Banking,
and
Financial
Markets
(Chapter
23).
Pearson.
Mishkin,
F.
S.,
&
Savastano,
M.
(2000).
Monetary
Policy
Strategies
for
Latin
America.
NBER
Working
Paper.
Mishkin,
F.
S.,
&
Schmidt‐Hebbel,
K.
(2007).
A
Decade
of
Inflation
Targeting
in
the
World:
What
Do
We
Know
and
What
Do
We
Need
to
Know?
In
F.
S.
Mishkin,
Monetary
Policy
Strategy.
Cambridge:
M.I.T
Press.
Mohanty,
M.
S.,
&
Turner,
P.
(2008).
Monetary
Policy
in
Emerging
Market
Economies:
What
is
New?
In
Transmission
Mechanisms
for
Monetary
Policy
in
Emerging
Market
Economies
(pp.
1‐60).
BIS
Papers
No.
35.
Mojon,
B.
(2000).
Financial
Structure
and
the
Interest
Channel
of
the
ECB
Monetary
Policy.
ECB
Working
Paper.
Moreno,
R.
(2008).
Monetary
Policy
Transmission
and
the
Long‐Term
Interest
Rate
in
Emerging
Markets.
BIS
Papers
,
61‐80.
Neumann,
M.
J.,
&
Hagen,
J.
v.
(2002).
Does
Inflation
Targeting
Matter.
Federal
Reserves
of
St.
Louis
Review,
127‐148.
Roger,
S.
(2010).
Inflation
Targeting
Turns
20.
Finance
and
Development,
46‐49.
Rose,
A.
K.
(2007).
A
Stable
International
Monetary
System
Emerges:
Bretten
Woods,
Reversed.
Journal
of
International
Money
and
Finance.
Sander,
H.,
&
Kleimeier,
S.
(2004).
Interest
Rate
Pass‐through
in
an
Enlarged
Europe:
the
Role
of
Banking
Market
Structure
for
Monetary
Policy
Transmission
in
Transition
Economies.
METEOR
Research
Memoranda
No.
045,
University
of
Maastricht
(Netherlands).
Sarwono,
H.
A.,
&
Warjiyo,
P.
(1998).
Mencari
Paradigma
Baru
Manajemen
Moneter
Dalam
Sistem
Nilai
Tukar
Fleksible:
Suatu
Pemikiran
Untuk
Penerapannya
di
Indonesia
(Searching
for
New
Paradigm
for
Monetary
Management
under
Flexible
Exchange
Rate
System).
Buletin
Ekonomi
Moneter
dan
Perbankan,
Vol.
1,
No.
1,
5‐23.
Schmidt‐Hebbel,
K.
(2009,
October).
Inflation
Targeting
Twenty
Years
on:
Where,
Why,
Which
Results,
What
Lies
Ahead?
Retrieved
January
2012,
from
www.economia.puc.cl:
http://eco3147.facea.puc.cl/economia_puc/docs/dt_360.pdf
Stiglitz,
J.
E.
(2008).
The
Failure
of
Inflation
Targeting.
Retrieved
February
2012,
from
Project
Syndicate:
http://www.project‐syndicate.org/print_commentary/stiglitz99/English
Stone,
M.
R.
(2003).
Inflation
Targeting
Lite.
IMF
Working
Paper.
33
Svensson,
L.
E.
(1997).
Inflation
forecast
targeting:
implementing
and
monitoring
inflation
targets.
European
Economic
Review,
1111‐1146.
Tieman,
A.
F.
(2004).
Interest
Rate
Pass‐Through
in
Romania
and
Other
Central
European
Economies.
IMF
Working
Paper.
Walsh,
C.
E.
(2009).
Inflation
Targeting:
What
Have
We
Learned?
University
of
California,
Santa
Cruz.
Warjiyo,
P.,
&
Agung,
J.
(2002).
Monetary
Transmission
in
Indonesia:
An
Overview.
In
P.
Warjiyo,
&
J.
Agung,
Transmission
Mechanisms
of
Monetary
Policy
in
Indonesia
(pp.
7‐26).
Jakarta:
Bank
Indonesia.
Warjiyo,
P.,
&
Zulverdi,
D.
(1998).
Penggunaan
Suku
Bunga
sebagai
Sasaran
Operasional
Kebijakan
Moneter
di
Indonesia
(The
Use
of
Interest
Rate
as
Operational
Target
of
Monetary
Policy
in
Indonesia).
Buletin
Ekonomi
Moneter
dan
Perbankan,
Vol.
1,
No.
1,
25‐58.
Weber,
A.
A.,
Gerke,
R.,
&
Worms,
A.
(2009).
Has
the
Monetary
Transmission
Process
in
the
Euro
Are
Changed?
Evidence
Based
on
VAR
Estimates.
BIS
Working
Papers
no.
276.
34
Table
1:
Inflation
Targeting
Countries
in
the
World,
1990­2008
Notes:
Adoption
dates
are
taken
from
Leyva
(2008)
Inflation
targets
are
taken
from
central
bank's
web
pages
The
middle
point
of
the
target
is
reported
when
the
inflation
target
is
defined
as
a
range
If
the
inflation
targeting
adoption
date
is
July
or
later
of
any
year
t,
the
annual
date
reported
is
year
t+1
E=emerging,
I=industrial,
S=stationary,
and
C=converging
Source:
Shmidt­Hebbel
(2009,
p.21)
35
Table
2:
Measures
of
Inflation
Deviations
from
Targets
and
Inflation
Deviations
in
IT
Countries,
from
IT
Starting
Quarter
through
2008IV
Notes:
Sample comprises inflation targets and inflation rates from the start of IT in each country until the fourth
quarter of 2008
Half-life of an inflation deviation are defined as the number of periods that a given inflation deviation from
target takes to converge to one-half its initial value
Half-lives are computed asumming that the best autoregressive process for inflation deviations for each
country is an AR(1)
MAE=Mean absolute error
36
MSE=Mean squared error
RMSE=Root mean squared error
Source: Shmidt-Hebbel (2009, p.27)
37
Figure
1:
Central
Bank
Transparency
Index
for
Country
Groups
by
Monetary
Policy
Regimes,
1998­2006
Note:
Transparency
index
ranges
from
0
(least
transparent)
and
15
(most
transparent).
Source:
Geraats
(2008),
based
on
data
by
Dincer
and
Eichengreen
(2007).
Figure
2:
Central
Bank
Transparency
Index
for
Industrial
and
EME
IT
Country
Groups,
1998­2005
Note:
Transparency
index
ranges
from
0
(least
transparent)
and
15
(most
transparent).
Source:
Geraats
(2008),
based
on
data
by
Dincer
and
Eichengreen
(2007).
38