The Anatomy of Monetary
Policy Transmission in an
Emerging Market
Kodjovi M. Eklou
WP/23/146
IMF Working Papers describe research in
progress by the author(s) and are published to
elicit comments and to encourage debate.
The views expressed in IMF Working Papers are
those of the author(s) and do not necessarily
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2023
JUL
* The author(s) would like to thank Andrés Fernández, Hou Wang, Katharina Bergant, Lamin Leigh, Modeste Some, Nada Choueri,
Tidiane Kinda, and Yan Carriere-Swallow and other participants to IMF seminars for helpful comments.
© 2023 International Monetary Fund WP/23/146
IMF Working Paper
Asia and Pacific Department
The Anatomy of Monetary Policy Transmission in an Emerging Market
Prepared by Kodjovi M. Eklou*
Authorized for distribution by Lamin Leigh
July 2023
IMF Working Papers describe research in progress by the author(s) and are published to elicit
comments and to encourage debate. The views expressed in IMF Working Papers are those of the
author(s) and do not necessarily represent the views of the IMF, its Executive Board, or IMF management.
ABSTRACT: Monetary policy transmission in EMs has been found to be weak historically due to under-
developed financial markets and heavy central bank intervention in FX markets that undermine the exchange
rate channel. Against this background, this paper investigates the transmission of monetary policy, including
the role of external factors, in Malaysia and highlight findings that could be relevant for other EMs. We find an
important role for the credit and the exchange rate channels. Further, we also find a complementary role for
policy tools including Foreign Exchange Intervention (FXI) and liquidity tools such as Statutory Reserve
Requirement in shaping the transmission of monetary policy. We then explore the spillover effects of external
global factors including global monetary policy and global commodity prices on monetary policy transmission in
a small open economy such as Malaysia. The results show that while global commodity prices do not impair
monetary policy transmission, global monetary policy tightening could complement domestic efforts to achieve
price stability by inducing a global disinflation. Finally, monetary policy transmission is delayed and weakened
in high inflationary environment, with the implication that more aggressive and preemptive policy actions may
be needed in such cases.
JEL Classification Numbers:
E3, E43, E52, E58, F4; O11; O22.
Keywords:
Monetary Policy; Emerging markets; Exchange rate; Credit; Inflation;
Economic activity; Global monetary policy.
Author’s E-Mail Address:
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The Anatomy of Monetary Policy
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Prepared by Kodjovi M. Eklou
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“The author(s) would like to thank” footnote, as applicable.
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Contents
Introduction ......................................................................................................................................................... 3
I. Identification of Monetary Policy Shocks .................................................................................................. 5
II. Empirical analysis of monetary policy transmission in Malaysia ..................................................... 8
A. Testing the channels of monetary policy transmission in Malaysia ...................................................... 8
B. Testing nonlinearities in monetary policy transmission in Malaysia: the role of domestic and external
factors ........................................................................................................................................................... 12
C. Testing the role of other policy levers: Foreign Exchange Interventions (FXI) and the Statutory
Reserve Requirement (SRR) ....................................................................................................................... 15
III. Conclusion ........................................................................................................................................... 18
Appendix. ........................................................................................................................................................... 19
References ......................................................................................................................................................... 25
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Introduction
Inflation has risen sharply to levels unseen for almost four decades in many economies, driven by a confluent
of factors including COVID-19 pandemic-related supply chain disruptions and rising commodity price shocks
amid Russian invasion of Ukraine.
1
After decades of loose monetary policy, central banks around the world
face important policy trade-offs such as striking a balance between managing inflationary pressures and
supporting nascent economic recovery. However, monetary policy transmission in emerging and developing
economies (EMDEs) has been found weak historically due to under-developed financial markets, heavy central
bank intervention undermining the exchange rate channel in FX markets (see Mishra et al, 2012), but also data
and methodological issues (see Berg et al., 2013). However, Brandão-Marques et al. (2021) shows that once
the exchange rate channel is explicitly accounted for, interest rate hikes reduce both inflation and output in
EMDEs. Further, monetary policy transmission in EMDEs depends on the policy framework, which is often
complex and opaque with multiple instruments and objectives (Berg et al, 2019), calling for the need to have
granular analyses on emerging economies to explore the potential peculiarities that may not be fully captured in
a cross-country sample.
This paper investigates monetary policy transmission in Malaysia, an emerging market economy that has
shifted to a market-based interest rate framework since May 2004. Following Romer and Romer (2004), we use
Monetary Policy Committee (MPC) meeting level data of the Bank Negara Malaysia (BNM), the central bank of
Malaysia, to estimate monetary policy shocks over the period May 2004 to July 2022.
2
We then use these
estimated shocks to investigate the transmission of monetary policy to inflation and economic activity in a local
projection framework (Jordá, 2005), similarly to Holms et al (2021). We ask the following research questions:
What are the main channels of monetary policy transmission in Malaysia? Is there any nonlinearity in the
transmission of monetary policy, including the level of the policy rate, the level of inflation, global supply side
pressures on inflation and global monetary policy tightening
3
? Is there a complementary role for other policy
tools such as Foreign Exchange Intervention (FXI) and liquidity tools such as the Statutory Reserve
Requirement (SRR) rate?
1
Headline CPI Inflation rate in Malaysia reached 4.65 percent in October in 2022 driven by food prices from a low-level pre-
pandemic (about 1 percent in December 2019).
2
The IMF (Country Report No. 2020/057) describes the policy reaction function of the BNM as “a multi-instrument reaction function
responding to multiple-indicator variables, including the exchange rate.” The principal tool for monetary policy in Malaysia is the
Overnight Policy Rate (OPR) with the Statutory Reserve Requirement (SRR) and open market operations also used to manage
liquidity. Further, the Bank Negara Malaysia’s (BNM) principal objectives are to preserve monetary and financial stability, with
the ultimate objective to promote sustainable growth. See IMF (2020) for additional detail on the monetary framework. The BNM
tightened monetary policy by increasing the overnight policy rate (OPR) five times since May 2022 by a total of 125 bps to 3.00
percent. Malaysia is not an Inflation targeter.
3
There is a large literature on the spillover effects of monetary policy in advanced economies, mainly the US, on emerging markets
(see for instance Rey, 2016; and, Miranda-Agrippino and Rey, 2020), which is outside the scope of this paper. The focus of this
paper is to investigate how global monetary policy affect domestic transmission in an emerging market economy.
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Using monthly data and explicitly modelling different channels of monetary policy transmission over the period
2004-2019, we find that the exchange rate and credit channels stand out. In particular, the exchange rate
channel features a strong, quick (about 7 months) and persistent transmission of monetary policy shocks to
inflation. The finding on the exchange rate channel is consistent with Brandão-Marques et al. (2021), as the
exchange rate plays an important role in emerging market economies given its large influence on demand in
small open economies and as a key variable for private sector expectations about inflation (see BIS, 2008).
We find similar results for economic activity (measured by industrial production index and unemployment rate),
with a low implied sacrifice ratio, that is the cost of output loss relative to price stability. The small sacrifice ratio
is also consistent with the relatively rapid pace of monetary policy transmission (in particular through the
exchange rate channel) but also given that the BNM is an independent central bank, and that Malaysia is an
open economy as identified by the literature on the determinants of the sacrifice ratio (see for instance,
Mazumder, 2014 and, Magkonis and Zekente, 2020).
Regarding nonlinearities, the paper shows that, while monetary policy transmission does not depend on the
level of the policy rate (OPR) or not affected by global supply side pressures on inflation
4
, the level of inflation
as well as the global monetary policy stance matter. More specifically, the paper uncovers that, monetary policy
transmission is delayed and weakened in high inflation context with the policy implication that there is a need
for a more aggressive and preemptive policy response in such contexts. Further, it shows that global monetary
policy tightening could complement domestic efforts toward price stability, but only if the former leads to a
global disinflation. Finally, it shows that policies such as liquidity tools and FXI can complement monetary policy
(in achieving price stability) in an emerging market economy such as Malaysia, as these strengthen
transmission. Consistent with the role of bank liquidity in shaping monetary policy transmission in Malaysia
(Rashid et al, 2020), the results show that tightening liquidity requirement through the SRR strengthens the
transmission. Finally, given the role of exchange rate channel, FXI plays an important complementary
especially when they lean against depreciations. FX purchases are found to amplify the credit channel of
monetary policy, consistent with Hofmann et al (2019) who find that FXI can affect domestic credit as
purchases could dampen credit to firms (in particular those vulnerable to currency movements). However,
these purchases tend to weaken the exchange rate channel. FX sales (that often takes the form of drawdown
in reserves), on the other hand, preserve the exchange rate channel with broadly neural impact on the credit
channel.
This paper brings novel insights on monetary policy transmission in EMs with important policy implications at
the current juncture characterized by high inflation and global tightening. The paper is closely related to Holms
et al (2021) and Brandão-Marques et al. (2021). It extends the framework in both papers to explicitly account
for different channels of monetary policy transmission and focuses on an emerging market to explore granular
4
Ha et al (2019) shows the importance of external shocks to domestic inflation dynamics in developing countries. Our finding
suggests that monetary policy can nevertheless deal with inflationary pressures originating from external supply side shocks.
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aspects of monetary policy including the role of complementary policy tools and global monetary policy stance.
To the best of our knowledge, this paper is the first, to investigate the implication of global monetary policy
tightening for domestic monetary policy transmission in an emerging market economy. Further, focusing on an
emerging market economy allows us to highlight the role of complementary tools as many EMs use multiple
tools to address shocks. Recent work by Cavallino (2019) emphasizes the role of FXI as a complementary
policy tool, but in the context of managing capital flows.
The paper contributes also more broadly to the literature on monetary policy transmission in emerging and
developing economies, including on Malaysia (see for instance Mishara et al, 2014; Khaw and Sivabalan, 2016;
Abuka et al, 2018; Poon, 2018; Barajas et al, 2018; Rashid et al, 2020).
5
For instance our results are consistent
with Abuka et al (2018) and Mishra et al (2014) who show the importance of the bank lending channel in
developing and emerging economies. Further, Barajas et al (2018) shows that remittances can weaken the
bank lending channel of monetary policy transmission by increasing liquidity in banks with their marginal cost of
loanable funds de-linked from movements in the policy rate in developing countries. Our finding on the SRR
suggests that central banks in developing countries could use liquidity tools to circumvent this challenge posed
by remittances. We also contribute to this literature by providing granular estimates of competing channels of
monetary policy channels, with an emphasis on the role of exchange rate channel, while previous work focused
on the bank lending channel in a cross-country sample. Recent empirical investigations on monetary policy in
Malaysia show the importance of the credit channel (Rashid et al, 2020)
6
, the asset price channel in particular
equity prices as captured by the stock market index (Khaw and Sivabalan, 2016) while Poon (2018) finds that
Capital Flow Measures (CFMs) reduced the transmission of monetary policy. These studies however do not
investigate explicitly the monetary policy transmission under the OPR regime as it is the case in this paper.
The remainder of the paper is organized as follows. Section I focuses on the identification of monetary policy
shocks, while section II is dedicated to the empirical analysis of monetary policy transmission in Malaysia
including the test of various channels, the nonlinearities, and the role of other policy levers. Finally, section III
concludes.
I. Identification of Monetary Policy Shocks
The first step in investigating the transmission of monetary policy is to identify monetary policy shocks.
Monetary policy decisions are usually endogenous because these decisions are made in response to current or
future economic conditions. To identify a causal effect of monetary policy, we need to isolate the component of
5
See for instance Mishra and Montiel (2013) for a comprehensive survey of the literature.
6
The authors use data on credit supply by banks to show that the credit channel is important in Malaysia, but Islamic banks respond
less to monetary policy compared to commercial banks. Further, they also find that small-sized banks respond more to the
increased interest rate as compared to large-sized banks. This finding holds for both Islamic and conventional banks. Finally,
less-liquid banks respond more to the tightening of monetary policy as compared to more-liquid counterparts.
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the change in the OPR that is not driven by the Central Bank’s expectation about key variables such as inflation
and growth. In this paper we follow the approach used in Romer and Romer (2004) and Holm et al (2021) to
identify these monetary policy shocks that are plausibly purged from expectations about economic conditions.
We exploit therefore the BNM monetary policy statement level data since the introduction of the market-based
interest rate framework in May 2004. Figure 1 shows historical OPR and changes in OPR by the BNM. Our
specification is similar to Holm et al. (2021) using data on policy meeting frequency as follows:
Where
is the change in the policy rate (OPR) at meeting m,
is the level of the OPR in the previous
meeting. Meeting m takes place in year t, and control variables include inflation forecasts for the current year (
and the next year (
, growth forecasts for the current and next year respectively
and
but
also the MYR/USD bilateral exchange rate from previous meeting month
.
7
Data on inflation and growth
forecasts were taken from the consensus forecast for the corresponding month of each meeting and the
bilateral exchange rate from CEIC. Finally,
is a measure of monetary policy shock associated with meeting
m obtained as a residual from equation (1).
Our estimates cover the meetings from May 2004 to July 2022. Table 1 shows the results of our estimates with
coefficients having expected coefficients and close to those found for the US and Norway by Romer and Romer
(2004) and, by Holm et al (2021) respectively. Further, similarly, the model explains about 30 percent of the
variation in the change in OPR (see Romer and Romer, 2004 and Holm et al., 2021). We find that, when the
BNM expects a strong growth in the current year, monetary policy rate is likely to be increased while it is likely
to hike the OPR when next year inflation is expected to be high. Figure 2 shows the estimated monetary policy
shocks (
from specification (1) in Table 1.
8
Following Romer and Romer (2004) and Holm et al (2021), we
obtain the monthly estimates of monetary policy shocks over January 2004 to July 2022, setting them to zero in
months without a monetary policy meeting.
7
We also use the lagged growth in the NEER (data from Haver) in an alternative specification and found very similar results.
8
The monetary policy shocks from specification (1) and (2) in Table 1 are very similar (correlation coefficient of 0.996).
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Figure 1: OPR and Changes in OPR
Table 1: Determinants of the changes in the OPR
(1)
(2)
-0.110***
-0.112***
(0.030)
(0.029)
0.024***
0.022***
(0.008)
(0.008)
0.029
0.024
(0.025)
(0.024)
-0.024
-0.020
(0.019)
(0.017)
0.113**
0.105***
(0.050)
(0.039)
0.011
(0.032)
0.002
(0.002)
-0.207
-0.122
(0.283)
(0.148)
N
115
115
R-squared
0.271
0.274
Robust standard errors in parentheses.
* p<0.10, ** p<0.05, *** p<0.01
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Figure 2: Monthly Monetary Policy Shock
II. Empirical analysis of monetary policy
transmission in Malaysia
A. Testing the channels of monetary policy transmission in Malaysia
Monetary policy transmission works through various channels including the interest rate channel, the exchange
rate channel, the bank lending (credit) channel and asset price channel.
9
First, an increase of nominal rates by
translating into higher real rates and user cost of capital lead to deferred consumption and reduction in desired
investment, thus exerting a downward pressure on prices through the interest rate channel. Second, the
exchange rate channel is also important in the context of open emerging markets and operates as follows. An
increase in domestic rates by leading to an appreciation puts downward pressure on prices of tradable goods in
the consumption basket. The exchange rate appreciation will also reduce both aggregate demand and net
exports. Third, through the credit channel, a tightening of monetary policy reduces deposits and liquidity from
the banking system and induces a reduction in lending. Finally, higher interest rates increase the discount
factor for future dividend income and could also reduce expected future cash flows and stock returns and thus
would reduce equity prices. Given the positive correlation between asset prices including equity prices and
consumption through a wealth effect, an interest rate hike would therefore reduce consumption and inflation.
9
The BNM highlighted these four channels as the most dominant for its monetary policy in a BIS survey (BIS, 2008).
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To test, the transmission channels of monetary policy in Malaysia, we use the previously identified monetary
policy shocks, and follow a specification similar to Holm et al. (2021) in a local projection framework (Jordá,
2005), robust to misspecification. We estimate the following equation:
Where
is the outcome variable (either the logarithm of the CPI index or the logarithm of the industrial
production index, as a proxy for output, or the unemployment rate), at time t (monthly data),
, is the
change in the logarithm of the nominal effective exchange rate (NEER),
is the year-on-year growth rate of
the stock market index,
is the change in commercial banks’ base lending rate and is a set of control
variables including the contemporaneous conditioning factors (
and
), two months of
lagged values of the dependent variable (logarithm of the CPI index and logarithm of the industrial production
index), 2 months of lagged values of the monetary policy shock
, two months of lagged values of
commodity price index, two months of lagged values of a proxy for foreign exchange intervention (FXI) and of
an index of US monetary policy uncertainty.
10
Finally, h=0,1..,24 is the horizon of cumulative response of the
dependent variable and
is the error term.
This specification augments the approach in Holm et al. (2021) and Brandão-Marques et al (2021) to explicitly
test the main competing channels of monetary policy transmission in Malaysia. Brandão-Marques et al (2021)
show that explicitly modelling the exchange rate channel of monetary policy allows to capture the effect of
monetary policy in emerging markets in a similar fashion to advanced economies. However, as previously
discussed, the BNM highlighted four main channels of monetary policy transmission including interest rate, the
exchange rate, the bank lending (credit) and asset price. We extend the specification in Brandão-Marques et al
(2021) by explicitly modelling two additional channels (asset prices and credit). In equation (2),
, captures the
cumulative impact of monetary policy shock on inflation, output, or unemployment rate at horizon h, when the
three channels of monetary policy transmission are shut down. Further, one can obtain the total impact of
monetary policy accounting for i) the exchange rate channel at one standard deviation in the change in the
NEER (σ) – about 1.2 percent appreciation – as
at horizon h, ii) the asset price channel at the 25
th
percentile of stock market index price growth (p25 ) – about -2.9 percent – as
and, iii) the credit
channel at a one standard deviation(φ) – about 7 basis points increase – in the base lending rate as
.
10
The lag selection was based on the Akaike and Bayesian information criteria. Further, the specification on industrial output uses 3
months of lagged values of the monetary policy shock and accounts for a structural break in the series around 2009:M2.
Following Holm et al. (2021), we smoothed the industrial production index. Data on industrial production index, CPI index, were
taken from International Financial Statistics, stock market index (FTSE Bursa MYSA composite) and base lending rate of
commercial banks from CEIC, FXI proxy data is taken from Adler et al. (2021) and US monetary policy uncertainty index from
Husted et al (2020). See Lakdawala et al (2021) who find a stronger spillover of US monetary policy uncertainty to bond yields in
EMs compared to US policy rates. Note that BNM counts FX market operations as part of monetary policy instruments with the
aim to mainly smooth ringgit movements (see BIS survey).
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Throughout the paper, we measure the outcome variable in deviation relative to its initial level in the month
preceding the shock and thus impacts shown should be interpreted as percent of initial month’s value. More
specially, outcome variables are the log change times 100. The policy shocks are measured as 1 percentage
point or 100 basis points (bps) change in month 0. The only exception is in the case of unemployment rate,
where the results are presented as a deviation in percentage points compared to the initial’s month value.
The impulse response functions (IRF) in Figure 3 show that, the effect of a 100bps increase in monetary policy
shock shutting off all channels, is negative and statistically significant only about 14-15 months and this effect
persists up to 21 months and can reach about 2.5 percent reduction in inflation. Focusing on the asset price
channel and testing for a potential amplifying effect of asset price movement yields a very similar IRF as in the
main effect. This suggests that the asset price channel is relatively muted. However, the IRF focusing on the
exchange rate channel shows larger impact on inflation in the short and long term. We find that in about 7
months, the same monetary policy shock could reduce inflation by 5 percent cumulatively. These effects could
persist and be larger in the long term (13 months – with a cumulative peak impact at about 8 percent). These
results imply that for an initial inflation rate of 3 percent, a 100bps tightening could lead to an inflation rate of
about 2.75 percent in 13 months. The credit channel on the other hand shows a cumulative reduction in
inflation by 3 percent in 18 months for the same magnitude of monetary policy shock. Overall, our finding is
similar to Brandão-Marques et al (2021) showing that the exchange rate channel is important for monetary
policy transmission in EMs.
11
The finding on the credit or bank lending channel is consistent with previous
literature (see for instance Mishra et al, 2014 and, Abuka et al., 2018).
11
The exchange rate plays an important role in emerging market economies given its the large influence on demand in small open
economies and as a key variable for private sector expectations about inflation (see BIS, 2008). We use credit growth as an
alternative measure to the base lending rate and found similar results for credit channel.
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Figure 3: Cumulative Impulse Response Function of a 100bps Monetary Policy Shock on
Inflation
Note: 90 percent confidence interval in dashed lines. Newey-West standard errors (robust to
autocorrelation) are used
Figure 4 shows our results for output response to monetary policy shocks. Our results show that a 100 bps in
monetary policy shock could reduce industrial production cumulatively by between 2 percent (main impact) to
about 3 percent in 24 months (when accounting explicitly for the credit channel or exchange rate channel).
These estimates, imply based on a back-of-the envelope calculation a reduction in real GDP by between 3.6
percent and 5.4 percent over 24 months respectively.
12
These estimates imply a sacrifice ratio close to one for
24 months.
13
Our results are close to Khaw and Sivabal (2016) who also found a low sacrifice ratio in
Malaysia. We also investigated the impact of monetary policy on unemployment rate (Figure A1 in Annex). We
find an increase in unemployment by about 2 percentage points in 24 months. Our finding on the small sacrifice
ratio is also consistent with the relatively rapid pace of monetary policy transmission (in particular through the
exchange rate channel) but also given that the BNM is an independent central bank, and that Malaysia is an
open economy.
14
12
Using quarterly data, we regress the logarithm of real GDP on the logarithm of industrial index production and found that industrial
production account for about 80 percent of the variation in real GDP over the period. Further, we found that a 1 percent increase
in industrial production implies a 1.8 percent increase in real GDP.
13
We calculate the sacrifice ratio as the ratio of the reduction in output over the reduction inflation.
In a shorter period (13 months),
the sacrifice ratio is below one. The sacrifice ratio is even lower considering the impact of monetary policy on unemployment
rate.
14
See for instance Mazumder (2014) and, Magkonis and Zekente (2020) showing that high speed of disinflation, greater central
bank independence and greater openness reduce the sacrifice ratio.
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Figure 4: Cumulative Impulse Response Function of a 100bps Monetary Policy Shock on
Industrial Production
Note: 90 percent confidence interval in dashed lines. Newey-West standard errors (robust to
autocorrelation) are used.
B. Testing nonlinearities in monetary policy transmission in Malaysia: the role
of domestic and external factors
In this section, we investigate the role of external factors (commodity prices and global monetary policy) as well
as domestic factors (high inflation and the level of the OPR) in shaping the transmission of monetary policy.
Focusing on the main channels of monetary policy transmission in Malaysia as identified in the previous
section, we consider the following equation:
Where
is a set of domestic factors (high inflation rate and the level the OPR) as well as external factors
(global commodity prices and global monetary policy), with now including two months lag values of these
domestic and external factors in addition to other controls consistently, while other variables retain the same
definition. We use the global commodity price index (as well as global food, energy and input price indexes as
a proxy for global supply side inflationary pressure) from the IMF. Drawing from the BIS policy rate statistics,
we measure global monetary policy as the average of change in policy rates weighted by each country’s
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currency share in global foreign exchange reserves.
15
We also investigate whether the monetary policy
transmission is affected by the level of policy rate and high inflation rates.
Our results in Figure A2 and A3 in the Appendix show that external supply side pressures on inflation as
captured through international commodity price dynamics (see Ha et al, 2019 on the role of external shocks in
driving inflation in developing countries), do not impair the ability of monetary policy to achieve price stability in
Malaysia. We test the impact of a 100 bps monetary policy shock conditional on a one standard deviation in
global commodity price inflation and found that there is no significant change to the baseline transmission
whether focusing on the credit or the exchange rate channel. We found similar results for global industrial input
price, global energy price and global food price inflation.
16
Our finding suggests that external supply side
pressures on inflation as captured through international commodity price dynamics, would not impair the ability
of monetary policy to achieve price stability in Malaysia.
Next, Figure 4 shows that global monetary policy tightening amplifies monetary policy transmission in Malaysia.
Our estimates of the impact of monetary policy shock in Malaysia conditioning on a 1 standard deviation –
about 13bps – hike globally shows that inflation could be cumulatively reduced by between 8 percent in 7
months (exchange rate channel) and about 10 percent (credit channel) in 18 months. Our findings suggest that
a synchronized tightening could have a persistent reduction effect on inflation up to 24 months, with all major
channels of monetary policy transmission amplified. We further investigate the channels through which global
monetary policy tightening could complement domestic effort to mitigate inflationary pressures in Malaysia. To
do so, we include global growth and global inflation among controls at different horizons.
17
We find that, once
we control for global inflation dynamics, the complementary role of global monetary policy is weakened (See
Figure A4 in Annex). This suggests that global monetary policy tightening would complement domestic efforts
only to the extent that it reduces global inflation. This finding is consistent with Ha et al. (2019) who show that
global inflation dynamics play an important role in shaping domestic inflation in developing countries. Further,
while there is a large body of the literature showing the negative spillovers of monetary policy in advanced
economies to EMs (see for instance Rey, 2016; and, Miranda-Agrippino and Rey, 2020), the paper shows a
novel result on how global monetary policy could affect domestic monetary policy effectiveness in maintaining
price stability.
15
This approach is similar to the Council on Foreign Relations’ methodology for their global monetary policy tracker. Our indicator
includes Australia, Canada, China, Euro area, Japan, Switzerland, United Kingdom, and United States. The currencies of these
countries represent about 97 percent of global foreign exchange reserves with the USD representing about 61 percent (data as
of 2022Q1).
16
We have also found (results not shown here) that while in general, monetary policy does not affect supply side inflation as
captured by the producer price index (PPI), considering the exchange rate channel, monetary policy can reduce PPI inflation in
Malaysia.
17
We applied Spline extrapolation to quarterly data from the IMF World Economic Outlook database to obtain monthly figures.
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We then, turn to test whether the impact of monetary policy depends on the level of the OPR and on the level
of inflation. We test the impact of a 100bps hike in the monetary policy shock conditioning on the median level
of the policy rate (of 3 percent) and found that there is no impact on the transmission compared to our baseline
finding (see Figure A5 in Appendix). This suggests that the transmission of monetary policy in Malaysia is
independent of the level of the policy rate. Further, we examine the role of high inflationary environment by
estimating the impact of a 100bps hike in the monetary policy shock conditioning on the level of inflation rate.
The estimates using the 75th percentile of inflation rate (3.2 percent) as a proxy for high inflation is shown in
Figure 6. The IRF shows that monetary policy transmission is weakened in high inflation environment. More
specifically, we find that the monetary policy transmission through the exchange rate is now delayed as we find
a statistically significant impact only around 13 months. In terms of magnitude, our results imply that the
effectiveness of monetary policy transmission could be reduced between about 20% (credit channel) and 30
percent (exchange rate channel) based on peak impacts. One implication is that in a period of high inflation,
monetary policy tightening may need to be more aggressive and preemptive to achieve the same result under
normal conditions but there could be also a delay in the transmission.
Figure 5: Synchronized Tightening and Monetary Policy Transmission to Inflation in Malaysia
Note: 90 percent confidence interval in dashed lines. Newey-West standard errors (robust to autocorrelation) are
used.
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C. Testing the role of other policy levers: Foreign Exchange Interventions
(FXI) and the Statutory Reserve Requirement (SRR)
In this section, we explore the role of other policy levers in shaping monetary policy transmission in Malaysia.
We employ a specification similar to equation (3) to investigate the role of FXI (one month lag) and SRR. As
discussed earlier, the BNM acknowledges FXI as being part of primary instruments of monetary policy albeit
with the sole aim to smooth ringgit movements. Given the importance of the exchange rate channel we test
how FXI interacts with monetary policy transmission in Malaysia. Further, while the BNM emphasizes that the
SRR should not be seen as a signal on the monetary policy stance it however stated that SRR can be used to
support the transmission of monetary policy rates to retail rates (see link). In addition, recent evidence (Rashid
et al, 2020) shows the importance of the liquidity condition of banks in shaping the transmission of monetary
policy in Malaysia.
Figure 6 shows the results for the role of changes in the SRR rate. Our IRF with the impact of a 100bps hike in
monetary policy shock estimated for 1 standard deviation in the change of the SRR – about 19bps – shows that
while the change in the SRR does not have material impact on the transmission through the exchange rate
channel it amplifies the credit channel, in particular in the medium term. We find a cumulative reduction in
inflation by 4 percent in 18 months compared to about 3 percent in the baseline estimates. This finding
suggests that liquidity tools could complement monetary policy in taming inflation in developing countries where
liquidity at banks play an important role in the transmission of monetary policy, as shown for countries highly
dependent on remittances (see for instance Barajas et al, 2018). Further, our finding is consistent with previous
finding that tightening of SRR leads to increased lending rates (Glocker and Towbin, 2012; and Kim and
Mehrotra, 2022).
Figure 6: High inflation environment and Monetary Policy Transmission to Inflation Malaysia
Note: 90 percent confidence interval in dashed lines. Newey-West standard errors (robust to autocorrelation) are
used.
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Finally, Figure 7 shows our results regarding how FXI affect monetary policy transmission with differentiation
between sales and purchases.
19
We find that FXI purchases amplify the credit channel, leading to a persistent
reduction in inflation with a cumulative impact (for a 1 percentage point of GDP increase) reaching about 4
percent reduction in inflation in 14 months (see Figure 7). This result is consistent with Hofmann et al (2019)
who find that FXI can affect domestic credit as purchases could dampen credit to firms (in particular those
vulnerable to currency movements). At the same time, by leaning against exchange rate appreciations, FX
purchases tend to weaken the exchange rate channel of monetary policy (see Mishra et al, 2012). Finally, we
find that sales preserve the exchange rate channel, by leaning against depreciations, with a broadly neutral
impact on the credit channel. Overall, consistent with Cavallino (2019) our finding suggests that FXI are a
complementary policy tool to monetary policy.
20
19
Figure A7 in Appendix shows FXI series.
20
Note however that Cavallino (2019) emphasizes the role of FXI as a complementary policy tool, but in the context of managing
capital flows within a DSGE framework with an application to Swiss data.
Figure 6: Statutory Reserve Requirement and Monetary Policy Transmission to Inflation in Malaysia
Note: 90 percent confidence interval in dashed lines. Newey-West standard errors (robust to autocorrelation) are
used.
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Figure 7: Foreign Exchange Intervention (FXI) and Monetary Policy Transmission in Malaysia
Note: 90 percent confidence interval in dashed lines. Newey-West standard errors (robust to
autocorrelation) are used.
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III. Conclusion
This paper investigates the transmission of monetary policy in Malaysia, a small open emerging economy over
the period 2004-2019 using monthly data. It shows that both exchange rate and the credit channels are
important for monetary policy transmission in this economy. While we find that monetary policy tightening
reduces both output and inflation, the relative cost of output loss to price stability is found to be low.
The paper uncovers important nonlinearities. First, the results show that in a high inflation context, monetary
policy transmission is weakened and delayed suggesting that a more aggressive and a preemptive policy rate
adjustment would need to be considered to have an impact similar under normal conditions. Second, global
monetary policy tightening amplifies monetary policy transmission with a larger reduction in inflation compared
to only a domestic policy tightening, driven by global disinflation. Third, in line with the importance of banking
sector liquidity in the transmission of monetary policy in Malaysia, we find that tightening the Statutory Reserve
Requirement (SRR) could amplify the impact of monetary policy tightening particularly through the credit
channel. Finally, FX purchase could strengthen the credit channel (although weakening the exchange rate
channel) while FX sales preserve the exchange rate channel.
This paper is the first, to the best of our knowledge to provide empirical evidence on the implication of global
monetary policy tightening for monetary policy transmission in a small open EM. It also brings novel insights on
monetary policy transmission in EMs with important policy implications at the current juncture characterized by
high inflation and global tightening. Further, it shines some light on whether global supply side pressures could
impede monetary policy transmission in a small-open economy. Finally, the paper brings also novel insights
regarding the complementarity of other policy tools in enhancing monetary policy transmission in an emerging
market.
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Appendix.
Figure A1: Cumulative Impulse Response Function of a 100bps Monetary Policy Shock on the
Unemployment Rate
Note: 90 percent confidence interval in dashed lines. Newey-West standard errors (robust to
autocorrelation) are used.
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Figure A2: Global Input and Energy Price - Monetary Policy Transmission to Inflation
Note: 90 percent confidence interval in dashed lines. Newey-West standard errors (robust to
autocorrelation) are used.
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Figure A3: Global Commodity Prices - Monetary Policy Transmission to Inflation
Note: 90 percent confidence interval in dashed lines. Newey-West standard errors (robust to
autocorrelation) are used.
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Figure A4: Channels of Global Monetary Policy Transmission to Inflation in Malaysia
Note: 90 percent confidence interval in dashed lines. Newey-West standard errors (robust to
autocorrelation) are used.
Figure A5: The Level of the OPR and Monetary Policy Transmission to Inflation in Malaysia
Note: 90 percent confidence interval in dashed lines. Newey-West standard errors (robust to autocorrelation) are
used.
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Figure A6: The Response of the Policy rate (OPR) to Monetary Policy Shocks
Note: 90 percent confidence interval in dashed lines. Newey-West standard errors (robust to
autocorrelation) are used. This Impulse Response shows how the level of OPR responds to a 100bps
monetary policy shock over the period 2004-2019 using monthly data.
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Figure A7: Foreign Exchange Intervention
Note: Data is taken from Adler et al. (2021) and Author’s calculation. Monthly series as percent of GDP.
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