INTEREST RATE PASS-THROUGH AND
BANKING MARKET INTEGRATION IN
ASEAN: A CROSS COUNTRY
COMPARISON
HAFEEZ UR REHMAN
Interest rate pass-through and banking
market Integration in ASEAN: A Cross
Country Comparison
Hafeez ur Rehman
Bachelor of Electronic Engineering
Ghulam Ishaq Khan Institute of Engineering Sciences
& Technology, Topi, Swabi
Pakistan
2004
Submitted to Graduate School of Business
Faculty of Business and Accountancy
University of Malaya, in Partial Fulfillment
of the requirements for the Degree of
Master of Business Administration (Finance)
2
Abstract
Inflation targeting has been the main policy objective for most of the central banks
around the world and the interest rate transmission has attracted much more attention
than ever before. Understanding of interest rate channel is crucial to uncover
monetary policy transmission mechanism.
This study deals with the interest rate pass-through, which is defined as the degree
and the speed of adjustment of retail bank rates to monetary policy interest rate, in
selected ASEAN Countries (Malaysia, Indonesia, Singapore, Philippines and
Thailand). The effectiveness of interest rate channel in economy is quantified by
analyzing the pass-through of interest rate from policy rate to retail banking rate.
Short term money market rate has been used as a proxy for the policy rate and various
deposit and loan rates of different maturities have been used for analysis. Unit root,
cointegration and Error correction Modeling has been applied on the data set to find
the short-run and long-run relationship between the interest rates. It has been found
that there is great amount of heterogeneity in the pass-through among various loan
and deposit categories. This difference is found both in terms of degree and speed of
adjustment. Indonesia and Philippines have the most effective interest rate
transmission mechanism, followed by Thailand, Singapore and Malaysia. The low
level of pass-through for Malaysia and Singapore can be attributed to the high level of
regulations in banking sector, high banking sector competition and high switching
costs. Research indicates a very low level of banking market integration for ASEAN.
3
Table of Contents
CHAPTER 1: INTRODUCTION ....................................................................................... 6
1
INTRODUCTION ...................................................................................................... 6
1.1
Research objectives ............................................................................................. 8
1.2
Problem Statement and Research Questions....................................................... 9
1.3
Scope of the study ............................................................................................... 9
1.4
Organization of the study .................................................................................. 10
CHAPTER 2: LITERATURE REVIEW .......................................................................... 11
2
LITERATURE REVIEW ......................................................................................... 11
CHAPTER 3: RESEARCH METHODOLOGY .............................................................. 22
3
RESEARCH METHOLOGY ................................................................................... 22
3.1
Economic Theory .............................................................................................. 22
3.2
Econometric Model ........................................................................................... 24
3.2.1
Unit root tests ............................................................................................ 25
3.2.2
Cointegration tests .................................................................................... 26
3.2.3
Error Correction Mechanism (ECM) ........................................................ 28
3.3
3.3.1
Data Analysis .................................................................................................... 29
3.4
Hypothesizing Coefficient Signs .............................................................. 29
Data Collection ................................................................................................. 30
3.4.1
Software implementation .......................................................................... 31
3.4.2
Sources of Data ......................................................................................... 32
CHAPTER 4: RESEARCH RESULTS ............................................................................ 33
4
RESEARCH RESULTS ........................................................................................... 33
4.1
Unit-Root Testing ............................................................................................. 33
4.2
Level-Degree of Integration .............................................................................. 34
4.3
Cointegration Testing........................................................................................ 36
4.4
Error Correction Model..................................................................................... 38
4.4.1
ECM-Philippines....................................................................................... 38
4.4.2
ECM-Malaysia .......................................................................................... 40
4.4.3
ECM-Thailand .......................................................................................... 42
4.4.4
ECM-Indonesia ......................................................................................... 44
4.4.5
ECM-Singapore ........................................................................................ 46
4
CHAPTER 5: CONCLUSION AND RECOMMENDATIONS ...................................... 50
5
CONCLUSION AND RECOMMENDATIONS ..................................................... 50
5.1
6
Interest Rate Pass-through: Cross Country Comparison .................................. 50
5.1.1
Indonesia ................................................................................................... 50
5.1.2
Philippines................................................................................................. 51
5.1.3
Thailand .................................................................................................... 51
5.1.4
Singapore: ................................................................................................. 52
5.1.5
Malaysia: ................................................................................................... 52
5.2
Interest Rate Pass-through: Cross Product Comparison ................................... 53
5.3
Banking Market Heterogeneity in ASEAN ...................................................... 54
5.4
Recommendations ............................................................................................. 55
REFERENCES ......................................................................................................... 56
APPENDIX-A................................................................................................................... 60
List of Figures
Figure 3-1 Econometric Model ......................................................................................... 24
List of Tables
Table 3-1 Interest Rate Data Information ......................................................................... 31
Table 3-2 Variables Name and Description ...................................................................... 31
Table 3-3 Sources of Data................................................................................................. 32
Table 4-1 Unit Root Testing ............................................................................................. 34
Table 4-2 Degree-Level of Integration Testing ................................................................ 35
Table 4-3 Engel-Granger Cointegration Test Stats ........................................................... 36
Table 4-4 Johansen Cointegration Test Stats .................................................................... 37
Table 4-5 Pass-through Stats Summary ............................................................................ 48
5
CHAPTER 1: INTRODUCTION
1 INTRODUCTION
The retail bank interest rate pass-through process is an important link in the process of
monetary policy transmission. Most central banks exert a dominant influence on a
country’s money market conditions and thereby, steer its money market interest rates.
The changes in money market interest rates in turn affect long-term market interest
rates and retail banks’ interest rates, although to varying degrees. In addition, bank
decisions regarding the yields paid on their assets and liabilities have an impact on the
expenditure and investment behavior of deposit holders and borrowers and thus, affect
real economic activity. In other words, a faster and fuller pass-through of official and
market interest rates to retail bank interest rates strengthens monetary policy
transmission. Furthermore, the prices set by banks do influence bank profitability and
consequently, the soundness of the banking system and its financial stability, which in
turn affect economic growth.
In order to ensure price stability for inflation targeting monetary policies, it is
essential for central banks to have a genuine and precise understanding of how fast
and to what extent a change in their interest instrument modifies inflation. In
particular, it is crucial to assess whether or not the pass-through from monetary policy
rates to long-term market and retail rates is complete, as this is the first building block
for monetary transmission mechanism. If interest rate pass-through is not complete,
the impact of monetary policy actions through the credit, interest rate or exchange rate
channels will also be considerably affected.
6
Against this backdrop, a large amount of past research has been dedicated to interest
rate pass-through in various countries but they have generally found them to be
incomplete and to react sluggishly to changes in the policy rate.
This paper aims to provide new insights into the determination of retail bank interest
rates in ASEAN. The main contribution of this study is that it is a precedent research
whereby both bank deposit rates and lending rates at the level of ASEAN are analyzed
by using more than one empirical method. In addition, another important factor
considered in this study is the banking market integration in the ASEAN region. This
analysis is based on the long run co-movement between monetary policy rate and
retail bank lending rates. Interest rate pass-through can be examined in two parts
which are short term and long term pass-through study. While high long-term pass
through which is expected to be close to one theoretically implies more effective
interest rate channel, it may also reflect the degree of competition among banks in the
credit market. Moreover, the speed of changes of lending rates may indicate market
players’ perception about monetary policy actions. These include the perception of
whether they are permanent or whether the market anticipates those policy decisions.
Thus, interest rate pass-through is not only critical for monetary policy, but it is also
important for the soundness of financial system as it includes serious implications for
both central bankers and financial supervisors.
Previous studies indicate that complete pass through in bank products is very rare in
the short run. In fact, most cases of adjustment are not completed even in the long run.
Most studies have discovered sluggish and incomplete adjustment of lending rates to
7
money market rates.1 In line with the empirical findings indicating incomplete pass
through, theoretical explanations have also been proposed to explain the
incompleteness of retail bank rates. The viscosity of interest rates can then be partly
explained by these theories.
1.1 Research objectives
The aim of the study is to analyze interest rate transmission channel in selected
ASEAN countries and its effectiveness of monetary policy for inflation targeting.
Using bank level data on interest rates of fixed deposits of different maturity, saving
deposits and base lending rates, the analysis is done for transmission of money market
interest rates to individual retail bank rates, where money market rate is taken as a
proxy of monetary policy rates. In addition, use of bank specific micro data allows
revealing the sources of heterogeneity in price setting behavior of banks in different
types of loans and deposits.
Most of the pass-through analyses done so far in the literatures have been focused on
European markets. To the best of my knowledge, this is the first attempt at finding the
retail banking market integration in selected ASEAN countries. Another unique
feature of this research is that the ASEAN market integration has been a popular topic
after the 1997 financial crisis, and various efforts are now on their way to have a
consolidated economy for the region. Thus, this study hopes to provide a better idea in
terms of how integrated the banking markets of the study’s selected ASEAN countries
are.
1
Sander and Kleimeier (2002 and 2004a-b)
8
1.2 Problem Statement and Research Questions
Inline with the research objectives, this research aims to answer the following main
questions:
 How effective is the interest rate transmission mechanism in selected ASEAN
countries?
 Are Pass-through rates same for all ASEAN Countries?
 How integrated is Banking Market in ASEAN?
 Is pass-through dependent on the type of bank products under study?
These questions will be discussed in detail in the respective analysis and conclusions
sections.
1.3 Scope of the study
Majority of recent literatures are related to the Euro Market Pass-through analysis for
various countries and the reason for the heterogeneity in the pass-through. The
primary focus of the studies was on the following two topics:
1. Pass through (short term and long term) analysis for various countries (for
various bank products) in a particular region.
2. Study of the factors contributing to the heterogeneity of pass through among
various countries and banking products.
However, this study is focused on the analysis of short-term and long-term pass
through for the selected ASEAN countries to explain the level of retail market
integration in the region. The reasons for the underlying heterogeneity in the pass
through for different banking products across countries is not part of the scope of this
research but should not be overlooked for a good future study.
9
For the purpose of this research, the following countries have been selected:
1. Malaysia
2. Indonesia
3. Singapore
4. Thailand
5. Philippines
A pass-through analysis for individual countries using its respective local currencies
and central bank statistics will be conducted. These are then compared with other
countries in the region to find out the heterogeneity in the banking market products as
well as among the countries.
1.4 Organization of the study
The organization plan for the rest of the report is as follows:
Section-2: Literature Review: This section details the relevant literature on the field
and various contributions by other researchers.
Section-3: Research Methodology: This section highlights the econometric models
in use for this analysis and the different kind of analytical tests to be performed.
Section-4: Data Analysis: This section details the actual results by applying the
econometric model to the data at hand.
Section -5: Conclusions and Recommendations: This last section highlights the
conclusions from this research and different recommendations based on the results.
10
CHAPTER 2: LITERATURE REVIEW
2 LITERATURE REVIEW
The interest rate pass-through can be separated into two stages. The first stage
measures how changes in the monetary policy rate are transmitted to short- and longterm market rates, while the second stage describes how changes in the market rates
influence bank deposit and lending rates. The first stage is to a large extent influenced
by the stability of the yield curve: If the term structure, whatever its form may be
(negative or positive sloping), remains stable over time, the pass-through from policy
rates to market rates is said to be proportionate. However, any twist in the yield curve
can change the size of the pass-through.
The cost of funds approach (DeBondt, 2005) is the best way to describe the second
stage of the interest rate pass-through, i.e. the connection between market rates on the
one hand, and bank deposit and lending rates of comparable maturity on the other
hand. In general, there are several factors which provide surety that market rates are
passed onto retail rates. For loan rates which are the link to market rates, is secured by
the fact that banks rely on the money market to fund (short-term) lending. This is in
the same vein that deposit rates which represent the cost of loans should be reflected
in loan rates. At the same time, yields on government securities can be viewed as
opportunity costs for banks. This helps maintain the link between, for instance,
government bond yields and loan rates of longer maturity. The connection between
market rates and deposit rates is warranted by the possibility that households and the
11
non-financial corporate sector can hold their financial assets not only in bank
deposits, but also in government securities of comparable maturity.
In addition, banks can rely on the money market instead of deposits for funding loans,
which can also lead to an equalization of deposit and money market rates. The
assumption of a stable yield curve makes it possible to take a shortcut by looking
directly at the relationship between policy rates and retail (deposit and loan) rates.
This approach is referred to as the monetary policy approach (Sander and Kleimeier,
2004a). The alternative transmission routes from policy rates to retail rates and the
ensuing empirically testable relationships are shown in table 1 below.
Table 1: Testable Relationships
Monetary Policy Approach
Policy rate → short-term/long-term deposit rate
Policy rate → short-term/long-term lending rate
Cost of Funds Approach
1st stage: yield curve
policy rate → 1m MMR → 12m MMR/T-bill rate → G-bond rate
2nd stage: cost of funds
a) 1m MMR / 12m T-bill/MMR → short-term deposit rate → short-term loans (long- term
loan rate)
b) 1m MMR / 12m T-bill/MMR → short-term loan rate (long-term loan rate )
c) GB rate → long-term deposit rate → long-term loan rate
d) GB rate → long-term loan rate
12
There could be a disproportionate pass-through from market rates to retail rates. If the
elasticity of demand for deposits, and for loans to the deposit and the lending rate
respectively, are lower than 1, the pass-through may not remain proportional.
Imperfect substitution between bank deposits and other money market instruments of
the same maturity (e.g. money market funds or T-bills) and between bank lending and
other types of external finance (equity or bond markets) may cause demand elasticity
to be lower than unity. Weak competition within the banking sector (i.e. among
banks) and in the financial sector (i.e. between banks and non-bank financial
intermediaries) reduces the sensitivity of the demand for deposits and loans to the
interest rate.2 High switching costs may also lead to lower demand elasticity.3
The magnitude of the pass through may also be impacted by macro-economic
conditions. It is generally observed that during periods of rapid economic growth, it is
easier and faster for banks to pass on changes in the interest rate to their lending and
deposit rates. Higher inflation rates also favor more complete and more rapid interest
rate pass-through, given that prices may be adjusted more frequently in a double-digit
or high inflation environment. By contrast, higher interest rate volatility (mirroring
higher macroeconomic instability and uncertainty) weakens the interest rate passthrough, given that banks wait longer before changing their rates. The pass-through
can not only remain incomplete in the long run, but has the tendency to remain
sluggish in the short run as well. There is a multitude of reasons for this. First,
adjustment or menu costs can cause banks to react sluggishly to changes in the market
2
The competition effect is more important for deposit rates than for lending rates, given that the former are less
affected by asymmetric information problems (Sander and Kleimeier, 2004a).
3
The pass-through can also be amplified , i.e. be higher than unity, if banks charge higher interest rates in an
attempt to offset the higher risks resulting from asymmetric information (adverse selection and moral hazard)
rather than reducing the supply of loans (DeBondt, 2005).
13
rates. Second, the maturity mismatch of banks’ loan and deposit portfolio influences
the way in which they adjusts their lending rates. The more long-term loans are
covered by long-term deposits, the less pressure banks feel to adjust their lending
rates, given that their liabilities are less sensitive to market rates (Weth, 2002).
Finally, given the long-term relationships of banks (especially universal banks) with
their customers, they may want to smooth interest rate changes.
Recent studies on interest rate pass-through differ according to whether they examine
individual or cross-country behavior. While some of the studies in the literature focus
on individual countries, others try to understand cross-country differences in interest
rate transmission relating possible variations to institutional framework or structural
breaks. All studies have an explicit aim, discovering the degree and speed of
adjustment of bank rates to changes in money market rates. Most studies cover
deposit rates, mortgage rates or bill rates in addition to retail lending rates. Regarding
the cross-country studies, BIS (1994), Borio & Fritz (1994), Cottarelli & Kourelis
(1995), Lowe (1994), Mozzami (1999), Mojon (2002), Kleimer and Sander (2000),
Donnay and Degryse (2001), Toolsema et al. (2001), Espinosa- Vega and Rebucci
(2003), and Bondt (2002) all find out that the dynamics of retail rate adjustment to
market interest rate changes are incomplete (i.e. changes in the market rates are not
reflected to lending rates completely). Second, the degree and speed of pass through
are different across particular retail rates. Lastly, there are significant differences
across countries, which can be attributed to macroeconomic or other country specific
factors (financial structure, banking competition, etc.). For single country cases,
Cottarelli et al. (1995) for Italy, Moazzami (1999) for Canada and United States,
Winker (1999) for Germany, Manzano and Galmes (1996) for Spain, and Bredin et al
14
(2001) for Ireland are some examples that focus on a particular country and
investigate banking system response to monetary policy actions by making use of
cointegration methods. Most of the studies in the literature base their analysis upon
the assumption that once the target for policy rate is changed, this will be reflected in
the changes in deposit rates, short-term market rates, bill rates and retail banking rates
sooner or later. Therefore, there is long run equilibrium among these variables. In
other words, these rates and monetary policy rate are co integrated. Thus, assessing
the degree and speed of adjustment of bank lending rates necessitates the use of an
empirical methodology examining both short and long run relationship between these
variables. In time series context, this is usually carried out with conventional
techniques, such as Engle-Granger two-step procedure, Johansen multivariate co
integration methodology or Autoregressive Distributed Lag (ARDL) model of Hendry
(1995). Re-parameterization of these approaches as an error-correction mechanism
allows for the estimate both short and long run parameters of pass through.
Bondt (2002) estimated an aggregate autoregressive distributed lag specification,
which is re-parameterized as an error-correction model for the euro area as a whole.
In the analysis, he used deposit and lending rates of different maturities with
government bond yields of similar maturities. He found that pass-through is
incomplete for both lending and deposit rates, reaching only 50 percent within a
month, but that completes in the end for most of the lending rates. It is worth
mentioning that use of micro data with panel method is very limited in the literature.
De Graeve et al. (2004), Sorensen and Werner (2006) and Horvat et al. (2004) are the
only current studies. De Graeve et al., for example, analyze the pass through of
market conditions to retail bank interest rates in Belgium with a panel of bank deposit
15
and loan rates. They measure the extent of pass-through for each product using panel
co-integration approach constructed in Pedroni (1995, 1997) and find out incomplete
pass through both for loans and deposit rates.
Most of the recent studies focused on the question whether there is a heterogeneous
pass-through (both in terms of the degree and the speed of adjustment) to bank
interest rates across the euro area countries, as well as across different interest rate
categories. The various studies differ widely in terms of scope and methods. For
example, some studies focus on aggregate interest rate series for individual countries
(or the euro area as a whole) typically using single-equation error-correction models
(ECM) to quantify the dynamics of the pass-through.4 Other studies use micro bank
data employing panel data techniques to examine the price setting behaviour of banks
in individual euro area countries.5 Previous studies also differ with respect to other
dimensions, such as the time period covered, data sources and the selection of the
exogenous market rate variable. As regards the latter, the majority of studies use a
money market rate as exogenous variable against which to measure the pass-through
to bank interest rates, although some more recent papers select a market rate of
comparable maturity in order to better reflect the marginal cost-of- funds
considerations inherent in banks’ rate-setting behavior.
Despite the diversity of approaches, a majority of the studies concludes that the
degree and speed of pass-through differ considerable across countries as well as
See Mojon (2000); Bredin, Fitzpatrick and O’Reilly (2001); Donnay and Degryse (2001); Heinemann and
Schüler (2002); Toolsema, Sturm and de Haan (2002); de Bondt, Mojon and Valla (2002); Sander and Kleimeier
(2002 and 2004a-b) for individual countries in the euro area; de Bondt (2002) for the euro area as a whole. See
also Cottarelli and Kourelis (1994) and Borio and Fritz (1995) for an international comparison as well as
Heffernan (1997) and Hofmann and Mizen (2004) for the UK and Berlin and Meister (1999) for the US.
5
See e.g. Cottarelli, Ferri and Generale (1995) and Gambacorta (2004) for the case of Italy; Weth (2002) for
Germany; and De Graeve, De Jonghe and Vennet (2004) for Belgium.
4
16
across banking products, especially in the short-run. The evidence of whether there is
full pass-through in the long-run is more scattered and so far no clear consensus has
emerged. However, at the same time, several studies document that differences in the
pass-through have converged somewhat and hence that the adjustment process of
bank interest rates to changes in market rates has become more homogeneous (and
speedier) among the euro area countries.6 Nevertheless, despite this relative
convergence all studies conclude that substantial heterogeneity in the pass-through
mechanism across countries and across bank products still remains. As regards the
latter, most studies suggest that rates on loans to enterprises and rates on time deposits
adjust relatively quickly, while rates on loans to households and rates on overnight
and savings deposits are relatively stickier.7 There seems to be a lesser degree of
consensus as regards the explanatory factors behind the pass-through heterogeneity.
Most studies relate it to structural differences in the financial systems, such as bank
competition; rigidity and size of bank costs; banking system ownership; monetary
polity regime; the extent of money market development; openness of the economy;
the degree of development of the financial system (i.e. competition from direct
finance) as well as the legal and regulatory system.
Mojon (2000) examined the pass-through in the six EMU countries for the period
1979-1998 for a whole range of deposit and credit rates (which can, however, not be
fully compared across countries) and confirms the conclusion of heterogeneity of
previous studies. Finally, Sander and Kleimeier (2001) provide evidence that the
6
See e.g. Mojon (2000); Toolsema, Sturm and de Haan (2002) and Sander and Kleimeier (2004a-b).
See Mojon (2000); Bredin, Fitzpatrick and O’Reilly (2001); de Bondt (2002), De Graeve, De Jonghe and Vander
Vennet (2004) and Sander and Kleimeier (2004a-b). The results of the studies are not uniform, which in part may
be due to differences in the exogenous market rates. 8 See Cottarelli and Kourelis (1994); Mojon (2000) and Sander
and Kleimeier (2004a-b) on determinants of the pass-through. A related strand of literature concerns the
determinants of bank margins: see e.g. Monti (1971); Klein (1971); Ho and Saunders (1981); Allen (1988);
Angbazo (1997); Saunders and Schumacher (2000) and Maudos and de Guevera (2004).
7
17
speed of adjustment and the nature of the adjustment process itself differ in the EMU
countries.
Cottarelli and Kourelis (1994) have also examined whether differences in passthrough are related to diverging financial structures. They obtain a significant
negative effect of five financial structure variables on the pass-through: the absence of
a money market for negotiable short-term instruments, the volatility of the money
market rate, constraints on international capital movements, the existence of barriers
to entry and the public ownership of the banking system.
Following Cottarelli and Kourelis (1994), Mojon (2000) has estimated the impact of
financial structure on the pass-through within a panel of 25 credit market rates and 17
deposit rates in the six biggest EMU countries. He finds that for both credit and
deposit rates the volatility of the money market rate reduces the passthrough and that
competition from direct finance increases it.
Some studies report evidence on interest rate stickiness for just one country. For
instance, Lowe and Rohling (1992) find large differences in pass-through in Australia
across different types of loans. They report complete pass-through of changes in
banks' marginal costs of funds only for overdraft rates to business borrowers. For
credit cards, personal loans, mortgages, and the standard overdraft rate, changes in the
banks' marginal costs of funds have not been translated one for one. This result
underlines that in analyses involving various countries one has to be very careful to
use as much as possible comparable interest rates. Cottarelli et al. (1995) conclude
that differences in the degree of lending rate stickiness among Italian banks are to a
18
large extent due to differences in concentration of the local markets in which banks
operate. Other relevant factors are: the extent of securitization of banks' liabilities, the
form of the loan, bank size and the banks' ownership structure.
Following the pioneering pass-through study by Cottarelli and Kourelis (1994) who
are applying a VAR model in an international context, this approach had soon been
adopted within the European context (Cottarelli, Ferri, and Generale 1995, BIS 1994,
Borio and Fritz 1995). Following Sander and Kleimeier (2000) pass-through studies
are now regularly based on an error-correction specification (e.g. Mojon 2000,
Heinemann and Schüler 2001, Toolsema, Sturm and de Haan 2002). Most recently,
asymmetric adjustment of retail bank rates to monetary impulses has also been
considered. This until now relatively small literature (see e.g. Sander and Kleimeier
2000, 2002, de Bondt 2002, 2 and de Bondt, Mojon, and Valla 2002) builds on Tong
(1983), Scholnick (1996, 1999), Balke and Fomby (1997), Enders and Granger
(1998), Baum and Karasulu (1998), and Enders and Siklos (2000).
The following pattern is generally observed in pass-through studies.
 Bank interest rates are sticky. Monetary policy rate changes typically lead to a
less than one-to-one change of retail rates, i.e. the short and medium-run
multipliers are taking values often far below unity.
 There are considerable differences in the pass-through across different bank
lending and deposit rates.
19
 While there is no consensus yet regarding a possible full pass-through in the
long run, most authors agree that the pass-through is next to complete with
respect to short-term lending to enterprises.
 Most studies find significant differences in the pass-through mechanism across
the different countries.
In Sander and Kleimeier (2003), they have tried to unify this research by arguing that
these differences are caused by predominantly differences in
(1) The choice of exogenous market interest rate.
(2) The length and timing of the investigated periods.
(3) The treatment of possible structural breaks.
(4) The chosen methodology for the pass-through study.
For the purpose of this research, individual country interest rate statistics will be used
from the period of 2000-2008 (Monthly interest rate). The details of the econometric
modeling have been given in the research methodology section.
The monetary policy approach has been used for this research and a one-month
money market rates are used. The choice of maturity is a matter of debate. So-called
cost-of-funds based studies are rooted in an industrial organization approach where
the market rate should reflect the marginal cost of funds. Thus, a matching and
possibly longer maturity is searched for. Studies that focus on monetary policy
transmission theories (the so called monetary policy approach) typically employ a
short-term market rate to avoid term structure of interest rates issues. Most authors
20
focus on the monetary-policy approach and use as a short-term money market rate the
1-month rate (Wro´bel and Pawłowska, 2002; Kot, 2004; Crespo-Cuaresma et al.,
2004; Chmielewski, 2004), (see e.g. Sander and Kleimeier, 2004a-b) and the same
approach has been followed in this research. The details of the econometric modeling
used are discussed in the next section.
21
CHAPTER 3: RESEARCH METHODOLOGY
3 RESEARCH METHOLOGY
Secondary data has been used in this study. The information regarding interest rates
for the different banks and their corresponding products have been gathered from the
central bank statistics, and from the respective individual banks.
For a comprehensive empirical analysis, monthly data for each of the banks products
for the year 2000 to 2008 for all the relevant countries have been selected. The exact
econometric methodology used for the analysis on this data can be seen in the
subsequent sections.
This section explains the economic theory which forms the basis of this study. The
variable and model selection process is also included to perform analysis of data.
3.1 Economic Theory
As mentioned earlier, this study intends to examine the pass-through effect of a
change in benchmark (or central bank) interest rate on retail banks in our bid to
understand the pass-through mechanism in monetary policy. Hence, the co-movement
between monetary policy rate and retail lending rates forms the basis of this analysis.
We are particularly interested in studying the proportion of pass-through (if any)
when there is a change in monetary policy rate, and how this will affect the various
banking products in retail banks.
Based on our observation and past researches, the interest rate pass-through from
central banks to retail banks is not necessarily proportionate as it depends on the
elasticity of demand for the banking products. Factors such as switching costs and
22
strength of competition will also determine the elasticity of the banking product but in
general, pass-through for lower elasticity is expected to be disproportionate.
In addition, macroeconomic conditions influence the size of the pass-through too. It is
observed that during periods of rapid economic growth, it is faster for banks to pass
on changes in the interest rate to their lending and deposit rates. Higher inflation rates
also favour more complete and more rapid interest rate pass-through, given that prices
may be adjusted more frequently in a double-digit or high inflation environment. By
contrast, higher interest rate volatility (mirroring higher macroeconomic instability
and uncertainty) weakens the interest rate pass-through, given that banks wait longer
before changing their rates.
Most studies relate it to structural differences in the financial systems such as bank
competition; rigidity and size of bank costs; banking system ownership; monetary
policy regime; the extent of money market development; openness of the economy;
the degree of development of the financial system (i.e. competition from direct
finance) as well as the legal and regulatory system.
The pass-through is expected to be complete in the long run and sluggish in the short
run. The reasons for this are manifold: First, adjustment or menu costs can cause
banks to react sluggishly to changes in the market rates. Second, the maturity
mismatch of banks’ loan and deposit portfolio influences the way in which they
adjusts their lending rates. The more long-term loans are covered by long-term
deposits, the less pressure banks feel to adjust their lending rates, given that their
liabilities are less sensitive to market rates (Weth, 2002). Finally, given the long-term
relationships of banks (especially universal banks) with their customers, they may
want to smooth interest rate changes to maintain such business relationship.
23
3.2 Econometric Model
Based on the above previous literatures, and as most of the interest rate time series in
our study are non-stationary in nature, we have chosen the following econometric
model for the purpose of this pass-through analysis.
Econometric Model
Unit
Unit Root
Root Test
Test
Stationarity
Cointegration
Cointegration Test
Test
Yes
EG,JJ, KPSS
No
ARDL
UECM
(Pesaran
et al.,
2001)
VECM
VAR in
differ
VAR in
Level
Model
Model Specification
Specification
Figure 3-1 Econometric Model
Note:
Unit-root test will be done for stationarity, followed by cointegration tests with the
Error Correction Model as the final step of analysis.
No pass-through analysis will be done for cases where the data are either stationary or
when no cointegration can be found.
24
3.2.1 Unit root tests
Interest rates are potentially non-stationary. In our analysis of the propagation of
market rates to bank interest rates, this has to be taken into account. As a result of the
study from Granger and Newbold (1974), it is known that a regression analysis using
non-stationary variables can easily end up with spurious results. The natural first step
is therefore to investigate the unit root properties of the variables under investigation.
To test for stationarity using unit root test, there are many tests available such as the
Dickey-Fuller (DF) Test, Augmented Dickey-Fuller (ADF) Test, Philips-Perron (PP)
Test, Dickey-Fuller Generalised Least Squares (DF-GLS), Ng and Perron (NP) and
KPSS or Kwiatkowski, Phillips, Schmidt, Shin (KPSS, 1992) among others.
In this research, Augmented Dicky-Fuller (ADF) test has been used to test for unitroot. It has been chosen for its simplicity of hypothesis and ease of understanding.
The normal DF Unit Root Test is based on the following three regression forms: \
1. Without Constant and Trend;
ΔYt = δYt-1 + μt
(1)
2. With Constant;
ΔYt = α + δYt-1 + μt
(2)
3. With Constant and Trend
ΔYt = α + βT + δYt-1 + μt
(3)
The hypothesis is:
H0: δ = 0 (unit root)
H1: δ ≠ 0 (series is stationary)
Decision rule:
If t* > ADF crtitical value, ==> do not reject null hypothesis, i.e., unit root exists.
25
If t* < ADF critical value, ==> reject null hypothesis, i.e., unit root does not exist.
Each of the equation will be run separately depending on the data specification.
To overcome the problem of autocorrelation in the basic DF test, the test can be
augmented by adding various lagged dependent variables which would produce the
following test:
m
yt  (   1) yt 1   i  yt i  ut
(4)
i 1
The correct value for m (number of lags) can be determined by reference to a
commonly produced information criteria such as the Akaike criteria or SchwarzBayesian criteria. The aim is to maximize the amount of information. The DF and
ADF test can also include a drift (constant) and time trend.
In order to confirm the unit-root tests, KPSS and Phillip-Perron tests will be used on
the interest rate data.
3.2.2 Cointegration tests
The degree and speed of adjustment in finance companies’ lending rates necessitates
the use of an empirical methodology examining both short and long run relationship
between these variables. In time series context, this is usually carried out with
conventional techniques, such as Engle-Granger two-step procedure, Johansen
multivariate cointegration methodology or Autoregressive Distributed Lag (ARDL)
model of Hendry (1995). Reparameterization of these approaches as an errorcorrection mechanism allows one to estimate both short and long run parameters of
pass-through. We will be using the first two approaches (Engel-Granger and Johansen
cointegration methodology) for our data analysis.
26
The basic idea behind cointegration is that if, in the long-run, two or more series
move closely together, even though the series themselves are trended, the difference
between them is constant. It is possible to regard these series as defining a long-run
equilibrium relationship, as the difference between them is stationary (Hall and
Henry, 1989). A lack of cointegration suggests that such variables have no long-run
relationship: in principal they can wander arbitrarily far away from each other
(Dickey et. al., 1991).
The time series are said to be cointegrated if the residual is itself stationary. In effect
the non-stationary I (1) series have cancelled each other out to produce a stationary I
(0) residual.
y t   0   1 xt  u t
(5)
Where y and x are non-stationary series. To determine if they are cointegrated, a
secondary regression is estimated to find the unit-root of the error term ut by ADF
test as follows (or any of the equations 1-3)
u t  u t 1  
(6)
If the critical value for this model is larger than the t-statistic, we would reject the null
hypothesis of non-stationary time series, and conclude that the error term was
stationary, and that the two variables are cointegrated.
In order to confirm our analysis, another Cointegration Test, Johansen Trace Test will
be used. This approach helps to determine the number of cointegrated vectors for any
given number of non-stationary variables of the same order. In other words, this is to
27
examine whether or not there exists a long run relationship between variables (stable
and non-spurious co-integrated relationship) (Miguel, 2000).
3.2.3 Error Correction Mechanism (ECM)
In order to model the two cointegrated non-stationary time series, we need to use
Error Correction Model. We will be using Engel-Granger ECM model and Johansen’s
model to find the Error correction terms. According to Engel-Granger, if two
variables y and x are cointegrated, then the relationship between the two can be
expressed as an Error Correction Model (ECM), in which the error term from the OLS
regression, lagged once, acts as the error correction term. In this case, the
cointegration provides evidence of a long-run relationship between the variables,
whilst the ECM provides evidence of a short-run relationship. A basic error correction
model would appear as follows:
yt   0  1xt   (ut 1 )   t
(7)
Where τ is the error correction term coefficient, which theory suggests should be
negative and whose value measures the speed of adjustment back to equilibrium
following an exogenous shock. The error correction term, which can be written as: is
the residual from the cointegrating relationship in (5)
We will use the secondary Vector Error Correction Model to cross-check the results
and come up with the conclusion.
28
3.3 Data Analysis
3.3.1 Hypothesizing Coefficient Signs
Inter Bank Offer Rate is generally the rate at which banks or financial companies’
lend to one another. As mentioned earlier, we will use 1-month Interbank rate as our
dependent variable.
The other choice of variables (Bank products) is as follows:
1. Inter Bank Offer Rate
2. Fixed Deposit -3 months Rate
3. Fixed Deposit -6 months Rate
4. Fixed Deposit -12 months Rate
5. Saving Deposit Rate
6. Base/Prime Lending Rate
i.
Relationship of IBOR with Fixed Deposit Rate and Saving account rates on
Financial Companies
As IBOR is influenced partly by the supply and demand for funds in the Interbank
market, it gives an indication of where deposit and savings account rates at financial
companies might be headed.
When liquidity in the market is tight and interbank rates rise, local financial
companies will offer more attractive rates to convince savers not to switch to foreign
rivals.
29
“When the money market interest rate rises, the deposit rate tends to rise more
slowly. On the other hand, when the money market rate falls, the deposit rate is
adjusted downward much more quickly.”
(Ref: Interbank Interest Rate Determination in Singapore and its Linkages to Deposit
and Prime Rate, Financial & Special Studies Division, Economics Department,
Moneytory Authority Of Singapore, September 1999, Pg 23)
The correlation between the IBOR and deposit rates tends to increase with the maturity of
the deposit rates.
Hence, in the long run, the expected signs of the coefficients for our testing on IBOR
with fixed deposit and saving account rates are expected to be positive.
ii.
Relationship of IBOR with Lending rates
IBOR’s movement will impact those loan packages which are pegged to the interbank
rate.
As IBOR falls, so too do the rate which adds up to cheap interest rates for lending. On
the other hand, if the Sibor rises, so too does the lending rate.
Again, in the long run, the expected sign of the coefficients for our testing on IBOR
with lending rate is expected to be positive.
3.4 Data Collection
All relevant data for the study is compiled from the Central Banks and Monetary
Authorities of selected countries on a monthly basis from January 2000 to December
30
2008. Using banking industry level data on interest rates of saving, time deposit and
loans extended to households and corporations, the analysis is done for transmission
of money market interest rates to individual retail financial companies’ rates, where
money market rate is taken as a proxy of monetary policy rates. In addition, the use of
banks specific micro data do allow disclosure of the sources of heterogeneity in price
setting behavior of banks in the different types of loans. Listed below is the list of
data used in this study. The details can be found in Appendix-A.
List of Data Used in the Study
Table 3-1 Interest Rate Data Information
Data type:
Time Series Data
Time period:
2000 – 2008
Frequency:
Monthly (108 data)
Table 3-2 Variables Name and Description
Data
Malaysia Interbank Rate (Monthly)
Singapore Interbank Rate (Monthly)
Philippines Interbank Rate (Monthly)
Bangkok Interbank Rate (Monthly)
Jakarta Interbank Rate (Monthly)
Banks Fixed Deposits - 3 mths
Banks Fixed Deposits – 6 mths
Banks Fixed Deposits – 12 mths
Banks Savings Deposit
Base/Prime Lending Rate
Symbol
KLIBOR
SIBOR
PHIBOR
BIBOR
JIBOR
FD3
FD6
FD12
SD
BLR
Variables
Independent
Dependent
3.4.1 Software implementation
In order to test the above mentioned econometric tests and hypothesis, Standard
Econometric package will be used. For most part of the data analysis, computation
will be done with EViews version 5, with some work done through SPSS.
31
3.4.2 Sources of Data
As all data is secondary, the central bank sites for the individual countries will be the
primary source of information and statistics for this analysis.
The summary of the sources can be seen from the following table:
Table 3-3 Sources of Data
DataBase
Website
Monitory Authority
of Singapore
http://www.mas.gov.sg
Bank Negara
Malaysia
http://www.bnm.gov.my
Bank of Thailand
http://www.bot.or.th
Central Bank of
Philippines
http://www.bsp.gov.ph
Bank Indonesia
http://www.bi.go.id
Bloomberg
http://www.bloomberg.com
32
CHAPTER 4: RESEARCH RESULTS
4 RESEARCH RESULTS
As mentioned in the Econometric Model section, the following tests will be done in
order to interpret the interest rate data that we have for the selected ASEAN countries
 Unit-Root Testing
 Level/Degree of Integration
 Cointegration Testing
o Granger and Johansen
 ECM Modeling
o Granger and Johansen ECM
4.1 Unit-Root Testing
As all interest rate time series need to be tested for unit root, the basic assumption for
calculating pass-through by Error Correction Modeling is that each series is non
stationary, and there is a long term relationship between the various interest rates i.e.
they are cointegrated.
Unit root testing has been done for the bank’s interest rates together with the market
rates for each loan/deposit category for a given period.
For the ADF unit-root test, the null hypothesis of unit root can not be rejected for any
of the variables. This is a first sign for non-stationarity of interest rates in the analyzed
period. It is therefore appropriate to model the interest rates using an error-correction
framework when there is a cointegration relationship between bank rates and market
rates.
The results for the unit root tests are summarized in the table below.
33
Table 4-1 Unit Root Testing
Singapore
Indonesia
Thailand
Philippines
Malaysia
Country
ADF Test
Stats
Test
critical
values:
1%
Test
critical
values:
5%
Test
critical
values:
10%
Durbin
Watson
Stats
Stationary
KLIBOR
-1.178164
-3.495677
-2.890037
-2.582041
1.999917
Non Stationary
FD3
-1.559615
-3.494378
-2.889474
-2.581741
1.911789
Non Stationary
FD6
-1.558505
-3.494378
-2.889474
-2.581741
1.734746
Non Stationary
FD12
-1.32556
-3.494378
-2.889474
-2.581741
2.001329
Non Stationary
UnitRoot
Test
SD
-1.634423
-3.494378
-2.889474
-2.581741
1.608003
Non Stationary
BLR
-1.081766
-4.048682
-3.453601
-3.1524
1.799916
Non Stationary
PHIBOR
-2.587551
-3.492523
-2.888669
-2.581313
2.043833
Non Stationary
FD3
-0.816653
-2.586753
-1.943853
-1.614749
1.854806
Non Stationary
FD6
-1.772917
-3.492523
-2.888669
-2.581313
1.895469
Non Stationary
FD12
-1.570396
-3.493129
-2.888932
-2.581453
1.978961
Non Stationary
SD
-2.647166
-4.046072
-3.452358
-3.151673
1.727153
Non Stationary
BLR
-2.183602
-3.493129
-2.888932
-2.581453
2.068224
Non Stationary
BIBOR
-1.145187
-3.493129
-2.888932
-2.581453
2.245185
Non Stationary
FD3
-2.308866
-3.495021
-2.889753
-2.58189
2.023176
Non Stationary
FD6
-1.771813
-3.493747
-2.8892
-2.581596
2.112415
Non Stationary
FD12
-1.704143
-3.493747
-2.8892
-2.581596
2.072585
Non Stationary
SD
-2.547201
-3.493129
-2.888932
-2.581453
1.982667
Non Stationary
BLR
-1.606732
-3.493747
-2.8892
-2.581596
2.034052
Non Stationary
JIBOR
-1.212506
-3.492523
-2.888669
-2.581313
2.065129
Non Stationary
FD3
-1.965084
-3.493747
-2.8892
-2.581596
2.053538
Non Stationary
FD6
-2.407267
-3.493129
-2.888932
-2.581453
2.139695
Non Stationary
FD12
-1.514631
-3.494378
-2.889474
-2.581741
1.990599
Non Stationary
SD
-1.224784
-3.501445
-2.892536
-2.583371
2.224726
Non Stationary
BLR
-1.351299
-3.493129
-2.888932
-2.581453
2.103588
Non Stationary
JIBOR
-1.108356
-2.586753
-1.943853
-1.614749
1.793821
Non Stationary
FD3
-1.991241
-3.493129
-2.888932
-2.581453
2.0433
Non Stationary
FD6
-1.945135
-3.493129
-2.888932
-2.581453
2.065087
Non Stationary
FD12
-1.987313
-3.493129
-2.888932
-2.581453
2.066547
Non Stationary
SD
-1.986585
-3.493129
-2.888932
-2.581453
1.952472
Non Stationary
BLR
-2.527367
-3.493129
-2.888932
-2.581453
1.856744
Non Stationary
4.2 Level-Degree of Integration
Another requirement for error correction model specification and the cointegration
evaluation is the degree of integration for the given variables. In order to measure the
degree of integration, uni-root testing is done at ‘level’, ‘the first difference’ and ‘the
second difference’ for all the variables.
34
The results of levels of integration for individual variables are given in the following
table.
It can be seen that all the variables are non-stationary at ‘level’ and stationary for ‘the
first difference’ i.e. they are I (1).
Table 4-2 Degree-Level of Integration Testing
Unit-Root
Country
Degree of
Integration
Malaysia
KLIBOR
FD3
FD6
FD12
SD
Philippines
BLR
PHIBOR
FD3
FD6
FD12
SD
BLR
Thailand
BIBOR
FD3
FD6
FD12
SD
BLR
Indonesia
JIBOR
FD3
FD6
FD12
SD
BLR
Singapore
SIBOR
FD3
FD6
FD12
SD
BLR
Level
First
Difference
Second
Difference
Degree of Integration
Non Stationary
Non Stationary
Non Stationary
Non Stationary
Non Stationary
Non Stationary
Stationary
Stationary
Stationary
Stationary
Stationary
Stationary
N/A
N/A
N/A
N/A
N/A
N/A
I(1)
I(1)
I(1)
I(1)
I(1)
I(1)
Non Stationary
Non Stationary
Non Stationary
Non Stationary
Non Stationary
Non Stationary
Stationary
Stationary
Stationary
Stationary
Stationary
Stationary
N/A
N/A
N/A
N/A
N/A
N/A
I(1)
I(1)
I(1)
I(1)
I(1)
I(1)
Non Stationary
Non Stationary
Non Stationary
Non Stationary
Non Stationary
Non Stationary
Stationary
Stationary
Stationary
Stationary
Stationary
Stationary
N/A
N/A
N/A
N/A
N/A
N/A
I(1)
I(1)
I(1)
I(1)
I(1)
I(1)
Non Stationary
Non Stationary
Non Stationary
Non Stationary
Non Stationary
Non Stationary
Stationary
Stationary
Stationary
Stationary
Stationary
Stationary
N/A
N/A
N/A
N/A
N/A
N/A
I(1)
I(1)
I(1)
I(1)
I(1)
I(1)
Non Stationary
Non Stationary
Non Stationary
Non Stationary
Non Stationary
Non Stationary
Stationary
Stationary
Stationary
Stationary
Stationary
Stationary
N/A
N/A
N/A
N/A
N/A
N/A
I(1)
I(1)
I(1)
I(1)
I(1)
I(1)
35
4.3 Cointegration Testing
Table-8 below summarizes the results for the cointegration tests. For banking interest
rates on saving deposits and lending rates, the null hypothesis of no-cointegration
cannot be rejected even at the 10% level. This is the same with interest rates for some
countries. Hence, it can be stated that the adjustment of interest rates to these interest
rate categories and countries is so sluggish that even a long-run relationship can not
be detected in our sample. For all other categories, bank interest rates seem to be
cointegrated with corresponding market rates.
In our specification model, we have used two kinds of tests to conclude cointegration.
They are:
1. Granger-Engel Cointegration Test
2. Johansen Cointegration Test
The results from both of these tests are summarized in the following two tables:
Table 4-3 Engel-Granger Cointegration Test Stats
Country
Granger
Cointegration
Test
Malaysia
FD3
FD6
FD12
SD
Philippines
BLR
FD3
FD6
FD12
SD
Stationarity
Non
Stationary
Non
Stationary
Non
Stationary
Non
Stationary
Non
Stationary
Non
Stationary
Non
Stationary
Non
Stationary
Non
Stationary
Trace Test
OLS
Level of
Residual
Integration Stationarity
Non
I (1)
Stationary
Non
I (1)
Stationary
Non
I (1)
Stationary
Non
I (1)
Stationary
Non
I (1)
Stationary
Cointegration
No
No
No
No
No
I (1)
Stationary
Yes
I (1)
Stationary
Yes
I (1)
Stationary
Yes
I (1)
Stationary
Yes
36
BLR
Thailand
FD3
FD6
FD12
SD
BLR
Indonesia
FD3
FD6
FD12
SD
BLR
Singapore
FD3
FD6
FD12
SD
BLR
Non
Stationary
Non
Stationary
Non
Stationary
Non
Stationary
Non
Stationary
Non
Stationary
Non
Stationary
Non
Stationary
Non
Stationary
Non
Stationary
Non
Stationary
Non
Stationary
Non
Stationary
Non
Stationary
Non
Stationary
Non
Stationary
I (1)
Stationary
Yes
I (1)
Non
Stationary
Non
Stationary
Non
Stationary
Non
Stationary
Non
Stationary
I (1)
Stationary
Yes
I (1)
Stationary
Yes
I (1)
Stationary
Non
Stationary
Non
Stationary
Yes
I (1)
I (1)
I (1)
I (1)
I (1)
I (1)
No
No
No
No
No
No
No
Non
Stationary
Non
Stationary
Non
Stationary
Non
Stationary
Non
Stationary
I (1)
I (1)
I (1)
I (1)
I (1)
No
No
No
No
No
Granger’s Cointegration test was found to have some inherent biases, thus, the same
data was used to detect cointegration through Johansen’s test. The results are
summarized below:
Table 4-4 Johansen Cointegration Test Stats
Trace Test
Thail
and
Philippines
Malaysia
Country
Max. Eigen Value Test
Max.
Eigen
Critical
Cointegration
Stats
Value
Equations
Johansen
Cointegration
Test
Trace
Stats
Critical
Value
Cointegration
Equations
FD3
12.58188
12.3209
1
12.43666
11.2248
1
FD6
13.64719
12.3209
1
13.43544
11.2248
1
FD12
12.83251
12.3209
1
12.74122
11.2248
1
SD
21.53734
12.3209
1
20.78972
11.2248
1
BLR
11.56603
12.3209
0
11.24471
11.2248
1
FD3
29.48448
12.3209
1
28.62068
11.2248
1
FD6
48.60642
12.3209
1
47.68928
11.2248
1
FD12
36.68277
12.3209
1
35.52946
11.2248
1
SD
39.22599
12.3209
1
38.13705
11.2248
1
BLR
16.52632
12.3209
1
16.06189
11.2248
1
FD3
12.71163
12.3209
1
12.70636
11.2248
1
FD6
11.70586
12.3209
0
11.70371
11.2248
1
37
Singapore
Indonesia
FD12
15.2245
12.3209
1
15.13248
11.2248
1
SD
13.6506
12.3209
1
13.62328
11.2248
1
BLR
12.51632
12.3209
1
12.43097
11.2248
1
FD3
90.74253
12.3209
1
90.55786
11.2248
1
FD6
110.9482
12.3209
1
110.777
11.2248
1
FD12
86.06436
12.3209
1
86.01492
11.2248
1
SD
33.21517
12.3209
1
33.0888
11.2248
1
BLR
38.77707
12.3209
1
38.60589
11.2248
1
FD3
16.23483
12.3209
1
15.40431
11.2248
1
FD6
16.24858
12.3209
1
15.39926
11.2248
1
FD12
17.08912
12.3209
1
16.20074
11.2248
1
SD
17.05311
12.3209
1
16.38565
11.2248
1
BLR
14.17985
12.3209
1
13.44421
11.2248
1
Since Johansen conintegration test is more robust as compared to Granger test, the
subsequent analysis will be based on the cointegration detected using Johansen’s tests.
4.4 Error Correction Model
As per the above analysis, it has been proven that there is cointegration between the
various fixed deposits and the money market rates. Hence, short and long term
relationship for interest rate pass-through for these products will be analyzed now. A
two level approach has been used in this section. They are the calculation of the short
and long term pass-through equation using ECM model by Engel-Granger as well as
the cointegration trace technique and ECM model by Johansen. The results have been
detailed in the following sections.
4.4.1 ECM-Philippines
1. Fixed Deposit 3 Months:
Granger’s ECM Model:
Long Term
FD3 = 0.8425993472 + 0.6188936709*PHIBOR
38
Short Term
D(FD3) = -0.006045690497 + 0.2778727288*D(PHIBOR) - 0.3170187116*UHAT(-1)
Johansen’s Model
Long Term
FD3 = 0.3461617839 + 0.7654157009*PHIBOR
Short Term
D(FD3) = - 0.2334462544*( FD3(-1) - 0.7654157009*PHIBOR(-1) + 0.3461617839 )
- 0.0118317757
2. Fixed Deposit 6 Months:
Granger’s ECM Model:
Long Term
FD6 = 0.6132233632*PHIBOR + 0.8693137472
Short Term
D(FD6) = -0.02544018159 + 0.07370702663*D(PHIBOR) - 0.3378425193*UHAT(-1)
Johansen’s Model
Long Term
FD6 = 0.7992309003*PHIBOR + 0.6214536304
Short Term
D(FD6) = - 0.3041939939*( FD6(-1) - 0.7992309003*PHIBOR(-1) + 0.6214536304 )
- 0.02818691589
3. Fixed Deposit 12 Months:
Granger’s ECM Model:
Long Term
FD12 = 0.5796371378 + 0.6969380836*PHIBOR
Short Term
D(FD12) = -0.03961028063 + 0.173597253*D(PHIBOR) - 0.2950187485*UHAT(-1)
Johansen’s Model
Long Term
FD12 = 0.8817724478*PHIBOR + 0.8962528113
Short Term
D(FD12) = - 0.2213659838*( FD12(-1) - 0.8817724478*PHIBOR(-1) + 0.8962528113
) - 0.04770093458
4. Saving Deposits:
39
Granger’s ECM Model:
Long Term
SD = -0.7274883573 + 0.6394030925*PHIBOR
Short Term
D(SD) = -0.03149150991 + 0.1136654883*D(PHIBOR) - 0.3459804882*UHAT(-1)
Johansen’s Model
Long Term
SD = 0.8049297577*PHIBOR + 2.052033591
Short Term
D(SD) = - 0.3002004849*( SD(-1) - 0.8049297577*PHIBOR(-1) + 2.052033591 ) 0.03644859813
5. Base Lending Rate:
Granger’s ECM Model:
Long Term
BLR = 7.062946074 + 0.3599329783*PHIBOR
Short Term
D(BLR) = -0.007681878973 + 0.08153907307*D(PHIBOR) - 0.4989575012*UHAT(1)
Johansen’s Model
Long Term
BLR = 0.4477067416*PHIBOR - 6.35671999
Short Term
D(BLR) = - 0.4744562817*( BLR(-1) - 0.4477067416*PHIBOR(-1) - 6.35671999 ) 0.009345794393
4.4.2 ECM-Malaysia
1. Fixed Deposit 3 Months:
Granger’s ECM Model:
Long Term
FD3 = 3.131130778 + 0.01034331869*KLIBOR
Short Term
D(FD3) = -0.003619542677 + 0.2692102267*D(KLIBOR) - 0.0307457633*UHAT(-1)
Johansen’s Model
40
Long Term
FD3 = 0.01761831585*KLIBOR - 3.108916318
Short Term
D(FD3) = - 0.04147317985*( FD3(-1) - 0.01761831585*KLIBOR(-1) - 3.108916318 )
- 0.001634615385
2. Fixed Deposit 6 Months:
Granger’s ECM Model:
Long Term
FD6 = 2.69233374 + 0.1704617574*KLIBOR
Short Term
D(FD6) = -0.004047623231 + 0.3397891433*D(KLIBOR) - 0.0357095995*UHAT(-1)
Johansen’s Model
Long Term
FD6 = 0.3860977589*KLIBOR - 2.026099224
Short Term
D(FD6) = - 0.04539747039*( FD6(-1) - 0.3860977589*KLIBOR(-1) - 2.026099224 ) 0.001538461538
3. Fixed Deposit 12 Months:
Granger’s ECM Model:
Long Term
FD12 = 4.49723549 - 0.2109417067*KLIBOR
Short Term
D(FD12) = -0.004583579186 + 0.309266113*D(KLIBOR) - 0.03117065194*UHAT(-1)
Johansen’s Model
Long Term
FD12 = 0.3660860376*KLIBOR - 4.97715109
Short Term
D(FD12) = - 0.04178929941*( FD12(-1) + 0.3660860376*KLIBOR(-1) - 4.97715109 )
- 0.002307692308
4. Saving Deposits:
Granger’s ECM Model:
Long Term
SD = 4.62130373 - 0.8789331066*KLIBOR
Short Term
D(SD) = -0.01319777459 + 0.1204418455*D(KLIBOR) - 0.002374266193*UHAT(-1)
41
Johansen’s Model
Long Term
SD = 28.83237316*KLIBOR - 91.01156786
Short Term
D(SD) = 0.0006669807262*( SD(-1) + 28.83237316*KLIBOR(-1) - 91.01156786 ) 0.01230769231
5. Base Lending Rate:
Granger’s ECM Model:
Long Term
BLR = 4.795996709 + 0.5294960938*KLIBOR
Short Term
D(BLR) = -0.003507857431 + 0.3808058751*D(KLIBOR) - 0.04094265998*UHAT(-1)
Johansen’s Model
Long Term
BLR = 1.048401977*KLIBOR - 3.191953082
Short Term
D(BLR) = - 0.03828397738*( BLR(-1) - 1.048401977*KLIBOR(-1) - 3.191953082 ) 0.0006730769231
4.4.3 ECM-Thailand
1. Fixed Deposit 3 Months:
Granger’s ECM Model:
Long Term
FD3 = 1.05119685 + 0.3691694465*BIBOR
Short Term
D(FD3) = -0.0126224734 + 0.1438365809*D(BIBOR) - 0.05811215145*UHAT(-1)
Johansen’s Model
Long Term
FD3 = 0.6977776545*BIBOR - 0.1115299125
Short Term
D(FD3) = - 0.05788060802*( FD3(-1) - 0.6977776545*BIBOR(-1) - 0.1115299125 ) 0.0108490566
2. Fixed Deposit 6 Months:
42
Granger’s ECM Model:
Long Term
FD6 = 0.9365278671 + 0.4267063439*BIBOR
Short Term
D(FD6) = -0.01149148644 + 0.1642590894*D(BIBOR) - 0.06200686128*UHAT(-1)
Johansen’s Model
Long Term
FD6 = 0.7155893467*BIBOR - 0.1100831678
Short Term
D(FD6) = - 0.06016489379*( FD6(-1) - 0.7155893467*BIBOR(-1) - 0.1100831678 ) 0.009433962264
3. Fixed Deposit 12 Months:
Granger’s ECM Model:
Long Term
FD12 = 1.065882708 + 0.4728119513*BIBOR
Short Term
D(FD12) = -0.01169400292 + 0.181846097*D(BIBOR) - 0.04880628258*UHAT(-1)
Johansen’s Model
Long Term
FD12 = 0.8649961552*BIBOR + 0.05570975131
Short Term
D(FD12) = - 0.04530697916*( FD12(-1) - 0.8649961552*BIBOR(-1) +
0.05570975131 ) - 0.009433962264
4. Saving Deposits:
Granger’s ECM Model:
Long Term
SD = 1.746274887 - 0.1753546496*BIBOR
Short Term
D(SD) = -0.01906738808 + 0.02164907258*D(BIBOR) - 0.02310663994*UHAT(-1)
Johansen’s Model
Long Term
SD = 0.1441180728*BIBOR - 0.8351919005
Short Term
43
D(SD) = - 0.02411198926*( SD(-1) - 0.1441180728*BIBOR(-1) - 0.8351919005 ) 0.01886792453
5. Base Lending Rate:
Granger’s ECM Model:
Long Term
BLR = 5.862405256 + 0.304697615*BIBOR
Short Term
D(BLR) = -0.00837035771 + 0.09315783773*D(BIBOR) - 0.05010132627*UHAT(-1)
Johansen’s Model
Long Term
BLR = 0.7609119494*BIBOR - 4.554431614
Short Term
D(BLR) = - 0.04924713173*( BLR(-1) - 0.7609119494*BIBOR(-1) - 4.554431614 ) 0.007075471698
4.4.4 ECM-Indonesia
1. Fixed Deposit 3 Months:
Granger’s ECM Model:
Long Term
FD3 = -0.1158129919 + 0.9578145385*JIBOR
Short Term
D(FD3) = -0.0159103675 + 0.1611267242*D(JIBOR) - 0.2832108294*UHAT(-1)
Johansen’s Model
Long Term
FD3 = 1.04361049*JIBOR + 1.089683526
Short Term
D(FD3) = - 0.2866170735*( FD3(-1) - 1.04361049*JIBOR(-1) + 1.089683526 ) 0.01579439252
2. Fixed Deposit 6 Months:
Granger’s ECM Model:
Long Term
FD6 = 1.310537342 + 0.8469078139*JIBOR
Short Term
D(FD6) = -0.02692778561 + 0.09411122233*D(JIBOR) - 0.187059503*UHAT(-1)
44
Johansen’s Model
Long Term
FD6 = 1.002583117*JIBOR + 0.444641171
Short Term
D(FD6) = - 0.1911236239*( FD6(-1) - 1.002583117*JIBOR(-1) + 0.444641171 ) 0.0285046729
3. Fixed Deposit 12 Months:
Granger’s ECM Model:
Long Term
FD12 = 3.530788157 + 0.7089170724*JIBOR
Short Term
D(FD12) = -0.0998189851 - 0.01805141652*D(JIBOR) - 0.1770038067*UHAT(-1)
Johansen’s Model
Long Term
FD12 = 0.9231452073*JIBOR - 1.118458328
Short Term
D(FD12) = - 0.1770421602*( FD12(-1) - 0.9231452073*JIBOR(-1) - 1.118458328 ) 0.101682243
4. Saving Deposits:
Granger’s ECM Model:
Long Term
SD = -0.2604857677 + 0.5383289234*JIBOR
Short Term
D(SD) = -0.05615397851 + 0.04017194683*D(JIBOR) - 0.05685147343*UHAT(-1)
Johansen’s Model
Long Term
SD = 0.7408213341*JIBOR + 2.488956094
Short Term
D(SD) = - 0.0561775313*( SD(-1) - 0.7408213341*JIBOR(-1) + 2.488956094 ) 0.05915789474
5. Base Lending Rate:
Granger’s ECM Model:
Long Term
45
BLR = 11.26703155 + 0.3824771586*JIBOR
Short Term
D(BLR) = -0.02695502455 + 0.02153462914*D(JIBOR) - 0.1091595173*UHAT(-1)
Johansen’s Model
Long Term
BLR = 0.5999056055*JIBOR - 8.818918272
Short Term
D(BLR) = - 0.1128643809*( BLR(-1) - 0.5999056055*JIBOR(-1) - 8.818918272 ) 0.02831775701
4.4.5 ECM-Singapore
1. Fixed Deposit 3 Months:
Granger’s ECM Model:
Long Term
FD3 = 0.5651679295 + 0.1152899321*SIBOR
Short Term
D(FD3) = -0.01109250174 + 0.05992159363*D(SIBOR) - 0.02075451904*UHAT(-1)
Johansen’s Model
Long Term
FD3 = 0.6898724212*SIBOR + 0.4787714018
Short Term
D(FD3) = - 0.01892914919*( FD3(-1) - 0.6898724212*SIBOR(-1) + 0.4787714018 ) 0.01205607477
2. Fixed Deposit 6 Months:
Granger’s ECM Model:
Long Term
FD6 = 0.7645083623 + 0.1076790393*SIBOR
Short Term
D(FD6) = -0.01334335213 + 0.05865719689*D(SIBOR) - 0.01983517199*UHAT(-1)
Johansen’s Model
Long Term
FD6 = 0.8244357702*SIBOR + 0.5376593848
Short Term
46
D(FD6) = - 0.01802823691*( FD6(-1) - 0.8244357702*SIBOR(-1) + 0.5376593848 ) 0.01429906542
3. Fixed Deposit 12 Months:
Granger’s ECM Model:
Long Term
FD12 = 0.9680745013 + 0.1264145691*SIBOR
Short Term
D(FD12) = -0.01525993244 + 0.0731686892*D(SIBOR) - 0.02183131227*UHAT(-1)
Johansen’s Model
Long Term
FD12 = 0.7429828898*SIBOR + 0.1513798683
Short Term
D(FD12) = - 0.02063067746*( FD12(-1) - 0.7429828898*SIBOR(-1) + 0.1513798683
) - 0.01644859813
4. Saving Deposits:
Granger’s ECM Model:
Long Term
SD = 0.371771298 + 0.06972393954*SIBOR
Short Term
D(SD) = -0.009824919124 + 0.03927307026*D(SIBOR) - 0.02312286041*UHAT(-1)
Johansen’s Model
Long Term
SD = 0.3707991053*SIBOR + 0.1746160156
Short Term
D(SD) = - 0.02273159459*( SD(-1) - 0.3707991053*SIBOR(-1) + 0.1746160156 ) 0.01046728972
5. Base Lending Rate:
Granger’s ECM Model:
Long Term
BLR = 5.319966372 + 0.05379904845*SIBOR
Short Term
D(BLR) = -0.003287233937 + 0.04230220669*D(SIBOR) - 0.03488194867*UHAT(-1)
Johansen’s Model
Long Term
47
BLR = 0.04850598195*SIBOR - 5.329421723
Short Term
D(BLR) = - 0.03830636916*( BLR(-1) - 0.04850598195*SIBOR(-1) - 5.329421723 ) 0.003925233645
From the data, it is quite clear that the speed of adjustment and the long term
multiplier is significantly different across different countries and deposit rates. The
summary of above statistics is given in the following table:
Table 4-5 Pass-through Stats Summary
Johanson
Long Term
Country
Pass
Through
Stats
Malaysia
FD3
FD6
FD12
SD
Thailand
Philippines
BLR
FD3
FD6
FD12
SD
BLR
FD3
FD6
FD12
SD
Singapore
Indonesia
BLR
FD3
FD6
FD12
SD
BLR
FD3
FD6
FD12
SD
BLR
Markup
Degree
of Pass
through
Granger
Short Term
Rate of
Adjustment
Long Term
Short Term
Markup
Degree
of Pass
through
Degree
of Pass
through
Rate of
Adjustment
-3.1089
-2.0261
-4.9772
91.0116
-3.1920
0.0176
0.3861
0.3661
-0.0415
-0.0454
-0.0418
3.1311
2.6923
4.4972
0.0103
0.1705
-0.2109
0.2692
0.3398
0.3093
-0.0307
-0.0357
-0.0312
28.8324
1.0484
0.0007
-0.0383
4.6213
4.7960
-0.8789
0.5295
0.1204
0.3808
-0.0024
-0.0409
0.3462
0.6215
0.8963
2.0520
-6.3567
0.7654
0.7992
0.8818
0.8049
0.4477
-0.2334
-0.3042
-0.2214
-0.3002
-0.4745
0.8426
0.8693
0.5796
-0.7275
7.0629
0.6189
0.6132
0.6969
0.6394
0.3599
0.2779
0.0737
0.1736
0.1137
0.0815
-0.3170
-0.3378
-0.2950
-0.3460
-0.4990
-0.1115
-0.1101
0.0557
-0.8352
-4.5544
0.6978
0.7156
0.8650
0.1441
0.7609
-0.0579
-0.0602
-0.0453
-0.0241
-0.0492
1.0512
0.9365
1.0659
1.7463
5.8624
0.3692
0.4267
0.4728
-0.1754
0.3047
0.1438
0.1643
0.1818
0.0216
0.0932
-0.0581
-0.0620
-0.0488
-0.0231
-0.0501
1.0897
0.4446
-1.1185
2.4890
-8.8189
1.0436
1.0026
0.9231
0.7408
0.5999
-0.2866
-0.1911
-0.1770
-0.0562
-0.1129
-0.1158
1.3105
3.5308
-0.2605
11.2670
0.9578
0.8469
0.7089
0.5383
0.3825
0.1611
0.0941
-0.0181
0.0402
0.0215
-0.2832
-0.1871
-0.1770
-0.0569
-0.1092
0.4788
0.5377
0.1514
0.1746
-5.3294
0.6899
0.8244
0.7430
0.3708
0.0485
-0.0189
-0.0180
-0.0206
-0.0227
-0.0383
0.5652
0.7645
0.9681
0.3718
5.3200
0.1153
0.1077
0.1264
0.0697
0.0538
0.0599
0.0587
0.0732
0.0393
0.0423
-0.0208
-0.0198
-0.0218
-0.0231
-0.0349
48
The ECM model provided some contradictory results, specifically for the short term
speed of adjustment. In addition, from the Engel-Granger cointegration analysis, it
was found that the speed of adjustment is too slow and the direction of adjustment is
also not constant. However, the Johansen trace tests and ECM model looks more
reliable and consistent with the economic theory. The results indicated that the speed
of adjustment is fastest for the 6-month and 3-month deposit rates with slower
adjustment when maturity increases to 12 months.
In addition to the above, the long-run multiplier is consistently higher for short
maturity deposit rates and lower for long term deposit rates. This is probably because
we are using short term money market rate as our dependant variable, hence, the short
term deposit rates are adjusted quickly to market competition. In contrast, long tem
maturity rates take some time to change but their change is smooth and even. The
long term multiplier for most cases is less than 1 indicating less than full passthrough. However, for Indonesia, there is some sort of over-shoot in the transmission
of interest rate from money market to retail market. It also has the best overall passthrough behavior among the list of countries. As for the other countries, Philippines
and Thailand do also have quite good pass-through behavior, with Malaysia and
Singapore having the weakest past-through behavior. The weak past-through behavior
in the two countries can be an indication of a high degree of competition in the retail
market for them. Overall the countries can be ranked as follows as per their passthrough behavior:
1. Indonesia
4. Singapore
2. Philippines
5. Malaysia
3. Thailand
49
CHAPTER 5: CONCLUSION AND
RECOMMENDATIONS
5 CONCLUSION AND RECOMMENDATIONS
There were three different aspects of interest rate transmission mechanism and banking
market heterogeneity which have been analyzed in this report. The results and
conclusions for each one of them will be highlighted in the following sections.
5.1 Interest Rate Pass-through: Cross Country Comparison
The primary result of this research is to study the variation in interest rate passthrough for all ASEAN countries. The analysis and their relevant conclusions for each
country are as below:
5.1.1 Indonesia
It has been found that among all the selected countries, Indonesia has an exceptionally
high pass-through rate. The long term pass-through rate for their fixed deposits is
almost equal to unity, even having results overshooting for their short term fixed
deposits.
In addition to the above, the rate of adjustment is around 20% per month for fixed
deposits, 6% for saving deposits and 11% for the lending rates respectively. All these
figures are considerably higher as compared to the data from other countries. This
indicates a highly efficient interest rate transmission mechanism and a very open
economy whereby their policy rate is totally and effectively transferred to the retail
banking consumer rates in a shortest period of time.
50
5.1.2 Philippines
Analysis on interest rate transmission mechanism in Philippines revealed some
interesting findings. Although the overall long term pass-through rate is considerably
high for Philippines, but the degree of pass-through behavior increases with maturity
of its fixed deposits.
Moreover the rate of adjustment is among the highest in ASEAN. It is around 23%
per month for fixed deposits, 30% for saving deposits and 47% for the lending rates
respectively. All these figures are considerably high as compared to the data from
other countries. This indicates that the interest rate transmission mechanism is quite
effective in Philippines and banks play a pivotal role in the transmission of monetary
policy.
5.1.3 Thailand
Thailand has been found to be quite effective in terms of long term transmission of
interest rates, but the speed of adjustment in the short run is quite sluggish.
Most of the bank products have quite high long term pass-through results with fixed
deposits and lending being more than 0.70. However, the saving deposits have long
term pass-through of 0.14 which indicates very minimal pass-through in the long run
and sticky interest rates for saving deposits.
Moreover, the rate of adjustment for the interest rates is not very high. The results do
indicate short term adjustment rate of 5-6% for fixed deposits and lending rates, but a
mere 2% for saving deposits.
This indicates that saving deposits are quite sticky and they do not change quickly in
response to the policy rate changes.
51
5.1.4 Singapore:
Although Singapore does not really follow inflation targeting as their monetary policy
objective, it has been included in the analysis to get an idea of how effective their
monetary policy in terms of transmission through interest rate channel.
The analysis indicates that the long-term pass-through, though not unitary, is quite
high (> 0.70) for their fixed deposit rates. However, it is quite low for their saving
deposits (0.37) and lending rates (0.048). It is interesting to note that the short term
rate of adjustment is quite low with mere 2% adjustment on monthly basis.
This indicates that the interest rate transmission mechanism in Singapore is not that
effective when it is compared to other ASEAN countries. This might be because of
high-switching costs for consumers and high competition in their banking industry. In
addition, their state policies do also contribute to the stickiness of their interest rates.
5.1.5 Malaysia:
It has been found that among all the selected countries, Malaysia has the lowest passthrough rate. Most of the time, series were cointegrated using a long lag, indicating an
inefficient interest rate transmission mechanism.
The long term pass-through rate for their fixed deposits was found to be 1%-26%
which is considered quite low from every standard. However, the short term rate of
adjustment is also at ~4%. This, however, does not imply that the Malaysian banking
and finance market is particularly inefficient. They can be indicative of a very high
degree of competition in their banking market. However, these banking interest rates do
react significantly to misalignments with corresponding market rates and consequently
adjust towards equilibrium, but at a slower rate for almost all of the short term interest
rate categories.
52
5.2 Interest Rate Pass-through: Cross Product Comparison
In terms of comparison across different banking products, results have been very
consistent and they do follow the general economic theory.
The fixed deposit rates are normally the ones having higher long term pass-through
and higher speed of adjustment in the short run. The results indicate that the speed of
adjustment is the fastest for the 3-month and 6-month deposit rates whereby it slows
down with the increase of its maturity to 12 months. Moreover, the long term passthrough is also more complete (the long run multiplier is closer to one) for shorter
maturity interest rates as compared to the long term deposit rates. This is probably
because we are using short term money market rate as our independent variable, so
the short term deposit rates are adjusted quickly to market competition, whereas the
long maturity rates take some time to change and change is smooth. The long term
multiplier for most cases is less than 1 indicating less than full pass-through.
The pass-through is considerably less for the saving deposits rate and lending rates,
which indicates that these rates are quite sticky and they do not move quickly to
adjust to policy rate changes. The short term speed of adjustment for the saving
deposits and lending rates is also quite low as compared to fixed deposit rates.
53
5.3 Banking Market Heterogeneity in ASEAN
The most important result of this study is the high degree of heterogeneity of the passthrough of market interest rates to banking interest rates in ASEAN countries. In addition
to the finding that there are differences in the pass-through rates across different
countries, it is also clear that both the long-run multipliers and the speed of adjustment
coefficients are different between various banking products. This suggests lack of
integration of the retail banking sector and financial institutions in this ASEAN
Countries.
This, however, does not imply that the banking and finance market is particularly
inefficient for the countries having a slower pass-through rate. It can be because of the
higher switching cost for the customers and very high degree of competition in the
banking market.
It is important to note that for the consolidation of ASEAN economies, it would be easier
for the countries with higher pass-through to adjust to the changes as compared to the
ones with lower pass-through rate. This is based on the fact that convergence of
economies results in the consolidation of banking sector and there is a central banking
authority to control all the regional entities, like the case with European Central Bank for
Euro Zone. The effectiveness of banking institutions, which have higher degree of passthrough and faster speed of adjustment, under a centralized authority will probably be
better as compared to the ones having a slower pass-through rate.
The research concludes that there is very low level of banking market integration in
ASEAN countries which will be a potential threat to their effective convergence in the
advent of banking sector consolidation.
54
5.4 Recommendations
This research has highlighted that there is very low level of banking market integration in
ASEAN countries which will make it potentially difficult for the individual countries to
effectively converge their banking sector. However, the differences have been identified
to be localized to individual countries in terms of their banking system, market
competition and consumer behavior. Thus, there is further room for research in finding
the ways to close this gap between the interest rate transmission behaviors for these
different countries. This is more so for the purpose of banking sector convergence in the
future.
Heterogeneity has been identified within each country for various banking products.
Though finding the exact causes of this heterogeneity is not within the scope of this
research but it will be interesting to understand the reasons behind the persistence of
heterogeneity, especially the differences in the speed of adjustment which could be a
natural next step to extend this analysis. This would improve the identification of
potential explanatory factors of the observed heterogeneity.
Another useful extension to this research could be the use of common foreign currency
(like USD, Euro) and find the pass-through for these foreign loans/deposits interest rates
for different countries. It will eliminate the effect of local banking authority and state
policies on the pass-through results which will then provide results that are more
comparable. However, getting all the required data for foreign currency bank products
can be a potential problem.
55
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 Cottarelli, C., Ferri, G., Generale, A., 1995. Bank lending rates and financial
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405–423
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 Horva´th, C., Kreko´ , J., Naszo´di, A., 2004. Interest rate pass-through: The
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Monetary Transmission in the New and Old Members of the EU, October 29–
30, 2004, Budapest.
 Horváth, Cs., J. Krekó and A. Naszódi. 2004. Interest Rate Pass-Through: The
Case of Hungary. National Bank of Hungary Working Paper 8.
 Johansen, S. 1995. Likelihood-Based Inference in Cointegrated Vector
Autoregressive Models. Oxford: Oxford University Press.
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European financial market integration: evidence from co-integration analysis.
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 Kleimeier, S., Sander, H., 2003. European financial market integration:
evidence on the emergence of a single eurozone retail banking market. Res.
Bank. Finan. 3, 13–91.
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 Mojon, B., 2001. Financial structure and the interest channel of the ECB
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Run and the Estimation of Transformed Regression Models. In: Economic
Journal 98. 189–205.
59
APPENDIX-A
Interest Rates: 2000-2008 for Selected ASEAN Countries
1. Singapore:
Singapore-Monthly Interest Rates
Fixed
Fixed
Fixed
Deposits
SIBOR 1
Deposits
Deposits
12
Months
3 Months 6 Months
Months
Period
2000
2001
2002
2003
Saving
Deposits
Prime
Lending
Rate
Jan
2.38
1.68
2.04
2.46
1.34
5.80
Feb
2.25
1.72
2.07
2.46
1.30
5.85
Mar
2.19
1.72
2.07
2.46
1.30
5.85
Apr
2.44
1.72
2.07
2.46
1.30
5.85
May
2.44
1.72
2.07
2.46
1.30
5.85
Jun
2.44
1.72
2.07
2.46
1.30
5.85
Jul
2.50
1.72
2.07
2.46
1.30
5.85
Aug
2.50
1.72
2.07
2.46
1.30
5.85
Sep
2.50
1.72
2.07
2.46
1.30
5.85
Oct
2.63
1.70
2.04
2.42
1.28
5.80
Nov
2.81
1.70
2.04
2.42
1.28
5.80
Dec
2.75
1.70
2.04
2.42
1.28
5.80
Jan
2.50
1.70
2.04
2.42
1.28
5.80
Feb
1.81
1.70
2.04
2.37
1.28
5.80
Mar
2.38
1.70
2.04
2.37
1.28
5.80
Apr
2.25
1.70
2.04
2.37
1.28
5.80
May
2.25
1.70
2.04
2.37
1.28
5.80
Jun
2.25
1.70
2.04
2.36
1.28
5.80
Jul
2.44
1.70
2.04
2.36
1.28
5.80
Aug
2.13
1.70
2.04
2.33
1.28
5.80
Sep
1.63
1.36
1.69
1.93
0.96
5.48
Oct
0.69
1.15
1.45
1.67
0.82
5.30
Nov
0.94
1.11
1.43
1.61
0.79
5.30
Dec
1.13
1.02
1.33
1.53
0.77
5.30
Jan
0.88
1.00
1.29
1.51
0.75
5.30
Feb
0.75
0.98
1.25
1.46
0.71
5.35
Mar
0.94
0.95
1.23
1.44
0.71
5.35
Apr
0.75
0.95
1.23
1.44
0.71
5.35
May
0.75
0.91
1.18
1.38
0.60
5.35
Jun
0.81
0.91
1.18
1.40
0.54
5.35
Jul
0.69
0.83
1.11
1.38
0.52
5.35
Aug
0.88
0.78
1.06
1.33
0.45
5.35
Sep
1.38
0.78
1.05
1.33
0.45
5.35
Oct
1.00
0.78
1.05
1.33
0.45
5.35
Nov
0.75
0.78
1.05
1.32
0.44
5.35
Dec
0.81
0.78
1.05
1.32
0.44
5.35
Jan
0.75
0.78
1.05
1.30
0.44
5.35
Feb
0.69
0.73
1.01
1.25
0.38
5.33
Mar
0.75
0.62
0.88
1.15
0.32
5.30
Apr
0.63
0.62
0.88
1.15
0.32
5.30
May
0.63
0.44
0.56
0.74
0.24
5.30
60
2004
2005
2006
2007
Jun
0.56
0.42
0.53
0.72
0.24
5.30
Jul
0.69
0.42
0.53
0.70
0.24
5.30
Aug
0.88
0.40
0.52
0.70
0.24
5.30
Sep
0.69
0.40
0.52
0.70
0.24
5.30
Oct
0.81
0.40
0.52
0.70
0.24
5.30
Nov
0.56
0.40
0.52
0.70
0.24
5.30
Dec
0.63
0.40
0.52
0.70
0.24
5.30
Jan
0.75
0.40
0.52
0.70
0.24
5.30
Feb
0.69
0.40
0.51
0.70
0.23
5.30
Mar
0.63
0.40
0.51
0.70
0.23
5.30
Apr
0.63
0.40
0.51
0.70
0.23
5.30
May
0.63
0.40
0.51
0.70
0.23
5.30
Jun
0.69
0.40
0.51
0.70
0.23
5.30
Jul
1.06
0.40
0.51
0.70
0.23
5.30
Aug
1.25
0.40
0.51
0.71
0.23
5.30
Sep
1.31
0.41
0.52
0.72
0.23
5.30
Oct
1.25
0.41
0.52
0.72
0.23
5.30
Nov
1.25
0.41
0.52
0.72
0.23
5.30
Dec
1.38
0.41
0.52
0.72
0.23
5.30
Jan
1.75
0.41
0.52
0.72
0.23
5.30
Feb
1.94
0.41
0.52
0.72
0.23
5.30
Mar
2.00
0.41
0.52
0.72
0.23
5.30
Apr
2.00
0.42
0.53
0.74
0.23
5.30
May
2.06
0.42
0.53
0.74
0.23
5.30
Jun
2.00
0.42
0.53
0.74
0.23
5.30
Jul
2.00
0.42
0.53
0.74
0.23
5.30
Aug
2.00
0.42
0.53
0.74
0.23
5.30
Sep
2.31
0.42
0.53
0.74
0.23
5.30
Oct
2.63
0.45
0.57
0.78
0.25
5.30
Nov
3.13
0.53
0.62
0.83
0.25
5.30
Dec
3.19
0.56
0.66
0.86
0.26
5.30
Jan
3.31
0.56
0.66
0.86
0.26
5.30
Feb
3.38
0.57
0.66
0.87
0.26
5.30
Mar
3.38
0.57
0.67
0.88
0.26
5.30
Apr
3.31
0.57
0.67
0.89
0.26
5.30
May
3.31
0.57
0.68
0.89
0.26
5.30
Jun
3.50
0.57
0.68
0.89
0.26
5.30
Jul
3.50
0.57
0.69
0.89
0.26
5.30
Aug
3.50
0.58
0.69
0.89
0.25
5.33
Sep
3.44
0.57
0.68
0.89
0.25
5.33
Oct
3.56
0.57
0.67
0.87
0.25
5.33
Nov
3.44
0.57
0.67
0.88
0.25
5.33
Dec
3.44
0.57
0.67
0.88
0.25
5.33
Jan
3.44
0.57
0.67
0.87
0.25
5.33
Feb
3.31
0.57
0.67
0.87
0.25
5.33
Mar
2.94
0.56
0.67
0.87
0.25
5.33
Apr
2.63
0.53
0.64
0.85
0.25
5.33
May
2.38
0.52
0.62
0.83
0.25
5.33
Jun
2.38
0.51
0.62
0.83
0.25
5.33
Jul
2.44
0.51
0.62
0.84
0.25
5.33
Aug
2.63
0.52
0.63
0.84
0.25
5.33
Sep
2.50
0.53
0.64
0.85
0.25
5.33
61
2008
Oct
2.38
0.51
0.62
0.84
0.25
5.33
Nov
2.31
0.51
0.62
0.83
0.25
5.33
Dec
2.00
0.51
0.62
0.83
0.25
5.33
Jan
1.69
0.48
0.59
0.79
0.25
5.38
Feb
1.38
0.46
0.55
0.74
0.24
5.38
Mar
1.13
0.42
0.52
0.71
0.24
5.38
Apr
1.25
0.41
0.51
0.71
0.24
5.38
May
1.06
0.42
0.52
0.71
0.24
5.38
Jun
0.94
0.41
0.53
0.73
0.23
5.38
Jul
0.88
0.40
0.54
0.74
0.23
5.38
Aug
1.00
0.39
0.53
0.73
0.23
5.38
Sep
1.88
0.41
0.53
0.73
0.23
5.38
Oct
1.13
0.43
0.55
0.73
0.23
5.38
Nov
0.69
0.41
0.55
0.73
0.23
5.38
Dec
0.75
0.39
0.51
0.70
0.22
5.38
2. Indonesia
JIBOR
-1
Month
Period
2000
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
2001
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
2002
Jan
Feb
Mar
Apr
11.95
11.63
11.40
11.29
11.36
12.06
13.19
13.39
13.52
13.70
14.14
14.70
14.90
14.97
15.62
16.21
16.38
16.75
17.34
17.72
17.74
17.81
17.78
17.85
17.41
17.28
17.15
16.96
Indonesia Monthly Interest Rates
Fixed
Fixed
Fixed
Deposits
Deposits
Deposits
12
3 Months 6 Months
Months
12.85
12.64
12.40
12.16
11.81
11.69
11.79
12.36
12.84
13.09
13.17
13.24
13.83
14.35
14.86
14.93
14.92
15.00
15.14
15.62
16.16
16.67
17.06
17.24
17.39
17.24
17.02
16.57
13.39
13.01
12.86
12.75
12.46
12.40
12.40
12.54
12.66
12.76
13.16
13.31
13.55
13.93
14.52
14.85
15.01
15.01
14.93
15.16
15.44
15.74
16.01
16.18
16.33
16.37
16.26
16.01
21.31
21.39
20.12
16.06
14.52
13.44
12.41
12.38
12.42
12.35
12.27
12.17
12.67
12.89
13.01
12.88
13.52
13.97
13.95
14.38
14.46
14.96
15.30
15.48
15.61
15.99
16.13
16.32
Saving
Deposits
Prime
Lending
Rate
8.95
8.98
9.04
9.06
9.04
9.03
9.11
9.13
9.20
9.22
9.22
9.19
9.28
9.26
9.30
9.29
17.43
17.14
16.46
16.30
16.54
16.21
15.86
15.79
16.62
16.78
16.94
16.59
16.77
16.88
16.86
16.80
16.85
17.04
16.90
17.08
17.22
17.38
17.64
17.90
17.99
18.01
18.03
18.09
62
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
2003
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
2004
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
2005
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
2006
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
16.08
15.73
15.25
14.73
13.28
13.61
13.52
13.45
13.10
12.62
11.89
11.58
10.97
9.95
9.43
9.20
8.85
8.67
8.69
8.55
8.16
7.71
7.56
7.42
7.37
7.44
7.38
7.40
7.40
7.40
7.42
7.44
7.42
7.45
7.46
7.51
7.87
8.33
8.71
10.56
11.68
14.15
13.19
13.56
13.19
13.15
13.03
13.01
12.67
12.67
12.47
11.86
16.24
15.85
15.26
14.77
14.36
13.94
13.76
13.63
13.49
13.15
12.90
12.48
12.02
11.55
10.65
9.58
8.58
7.96
7.58
7.14
6.68
6.38
6.11
6.01
6.17
6.31
6.49
6.54
6.61
6.65
6.66
6.71
6.71
6.74
6.93
6.87
7.03
7.19
7.41
7.71
8.51
9.38
10.72
11.75
12.23
12.32
12.19
12.03
11.82
11.70
11.57
11.34
15.83
15.73
15.55
15.18
14.81
14.46
14.13
13.79
13.62
13.51
13.22
13.01
12.63
12.21
11.63
11.10
10.47
9.85
9.21
8.25
7.63
7.14
6.79
6.45
6.35
6.36
6.43
6.70
6.89
6.99
7.06
7.12
7.08
7.24
7.35
7.10
7.11
7.11
7.29
7.44
8.01
8.62
9.39
10.17
11.18
11.70
12.10
12.20
12.20
12.09
11.97
11.79
16.31
16.28
16.25
16.07
15.99
15.76
15.52
15.28
15.09
14.61
14.16
13.67
13.34
12.93
12.76
12.24
11.90
11.30
10.93
10.39
9.96
9.59
8.93
8.25
7.90
7.68
7.46
7.30
7.27
6.98
7.04
7.07
7.06
7.11
8.04
7.09
7.16
7.11
7.30
7.46
8.65
9.21
9.60
10.95
11.47
11.90
12.02
12.14
12.20
12.28
12.36
12.38
9.27
9.27
9.27
9.20
9.19
9.03
8.94
8.96
8.81
8.71
8.43
8.27
8.16
7.46
6.67
6.26
5.84
5.71
5.41
5.14
4.91
4.69
4.62
4.49
4.47
4.45
4.40
4.35
4.34
4.35
4.30
4.37
4.16
4.14
4.13
4.18
4.16
4.15
4.13
4.15
4.42
4.59
4.80
4.85
4.84
4.84
4.90
4.84
4.86
4.85
4.83
4.84
18.11
18.11
18.09
18.10
18.11
18.00
18.00
17.82
17.82
17.85
17.85
17.74
17.67
17.43
17.03
16.70
16.53
16.27
15.93
15.68
15.44
15.29
15.12
14.98
14.78
14.64
14.58
14.45
14.33
14.25
14.18
14.05
13.98
13.87
13.78
13.74
13.68
13.65
13.65
13.62
14.47
14.92
15.43
15.66
15.81
15.87
15.90
15.90
15.89
15.94
15.91
15.85
63
Sep
Oct
Nov
Dec
2007
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
2008
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
11.29
10.79
6.69
9.49
9.05
8.94
9.04
8.81
8.63
8.26
5.65
7.92
7.97
8.06
7.94
7.95
8.01
7.94
8.04
8.00
8.37
8.86
9.45
9.62
10.77
11.75
11.72
11.40
11.05
10.72
10.25
9.71
9.26
8.83
8.52
8.30
8.06
7.87
7.69
7.51
7.44
7.41
7.40
7.42
7.40
7.36
7.26
7.23
7.34
7.49
7.82
8.40
9.45
10.17
10.83
11.16
11.52
11.26
10.98
10.70
10.27
9.80
9.29
8.89
8.59
8.40
8.20
8.00
7.80
7.76
7.70
7.65
7.62
7.59
7.57
7.57
7.64
7.79
8.08
8.43
9.14
9.50
9.97
10.34
12.36
12.28
12.18
11.63
11.20
10.47
10.17
9.90
9.68
9.54
9.32
9.11
8.91
8.73
8.60
8.24
8.11
7.88
7.79
7.70
7.71
7.78
8.23
8.51
9.34
9.67
9.95
10.43
4.77
4.58
4.51
4.38
4.22
4.13
4.05
3.79
3.62
3.58
3.55
3.55
3.54
3.46
3.46
3.48
3.42
3.30
3.27
3.23
3.24
3.24
3.23
3.23
3.25
3.30
3.31
3.33
15.66
15.54
15.38
15.10
14.85
14.71
14.53
14.38
14.16
13.99
13.82
13.75
13.45
13.28
13.19
13.01
12.81
12.71
12.59
12.47
12.36
12.51
12.61
12.86
13.32
13.88
14.28
14.40
3. Philippines:
Philippines Monthly Interest Rates
Fixed
Fixed
Fixed
Deposits
Deposits
Deposits
12
PHIBOR
3 Months
6 Months
Months
Period
2000
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
2001
Jan
Feb
9.3869
8.9625
9.1193
9.0000
9.4318
9.4792
9.4137
9.7582
11.5119
19.3665
18.1701
17.0188
15.0455
12.8000
6.994
7.001
7.306
5.518
6.800
7.424
7.580
7.269
7.503
12.007
12.782
11.477
10.423
9.674
7.194
8.186
7.128
5.620
7.152
7.615
7.434
7.530
8.480
9.119
12.712
11.604
10.555
9.370
8.858
8.762
8.760
8.307
8.534
8.579
8.472
8.637
8.810
9.600
13.539
12.550
11.918
10.715
Saving
Deposits
Prime
Lending
Rate
6.4
6.2
6.4
6.3
6.5
6.4
6.7
6.7
6.4
7.8
10.8
11.2
9.7
8.9
10.3
10.2
10.6
10.3
10.1
10.6
10.3
10.9
11.6
10.7
12.4
13.1
12.8
11.8
64
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
2002
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
2003
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
2004
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
2005
Jan
Feb
Mar
Apr
May
Jun
11.5852
11.9653
11.5327
10.3344
9.9034
10.7989
13.1531
12.1957
11.7993
15.8750
8.5227
7.7039
6.9079
5.9970
5.4517
5.7763
6.7670
6.9631
6.3512
6.4489
6.2250
6.9081
6.7813
7.5197
7.9732
9.9342
7.9344
8.1563
7.9946
7.0625
7.1534
6.9321
7.3849
7.9539
7.2125
8.7566
8.6332
8.3388
7.4219
7.2202
7.2159
6.9148
7.1534
7.0982
6.7708
7.3611
7.0089
5.8586
5.8938
5.8958
4.7321
6.2857
9.434
8.184
8.747
7.840
7.957
8.149
8.034
8.509
9.291
8.688
8.313
7.092
6.714
3.762
3.744
3.416
4.168
3.102
3.573
4.077
3.294
4.041
3.731
4.101
5.124
5.981
6.523
6.009
5.309
5.100
4.753
5.023
5.769
5.225
5.277
5.223
6.142
5.816
5.578
6.445
6.938
6.467
6.349
6.720
6.606
6.569
6.367
5.901
5.434
5.600
5.201
5.047
9.388
8.263
8.981
8.310
8.143
8.529
7.742
9.876
10.175
9.456
10.056
8.825
7.682
5.627
4.926
4.734
4.818
4.806
4.759
4.946
4.678
4.852
4.789
4.865
4.941
5.108
4.973
5.336
4.965
4.714
5.006
5.703
5.151
5.479
4.946
5.023
5.402
5.498
5.434
5.871
5.935
6.121
5.831
6.630
6.106
6.849
6.170
5.513
5.515
5.408
5.199
5.025
9.969
9.633
9.644
8.805
8.859
9.312
9.269
9.609
9.791
8.797
7.953
7.112
5.831
4.647
5.251
4.098
4.093
4.188
4.157
4.122
4.215
4.563
4.822
5.096
5.178
5.916
6.394
6.138
5.710
5.638
5.812
5.551
6.106
6.100
5.915
5.699
6.709
6.187
5.303
5.251
5.866
6.643
7.059
6.752
6.535
6.317
6.740
5.057
7.924
6.400
5.694
5.650
9.8
7.2
7.1
6.5
6.6
6.7
6.9
8
7.1
7.3
7.2
5.6
5.6
4.4
3.6
3.4
3.5
3.5
3.4
3.6
3.5
3.6
3.7
3.5
4.2
4.7
5.3
5.2
4.3
4
3.8
3.9
3.8
4.1
4.1
3.7
4.2
4.2
4.4
4.2
4.4
4.4
4.1
4.5
4.4
4.4
4.5
3.6
3.8
3.5
3.7
3.6
12.2
11.6
14
11.1
10.9
12.9
12.2
14.5
11.9
13
12
9.9
10.5
9.6
8.6
8.7
8.6
8
7.9
8.9
8.5
8.5
8.8
8.1
9.4
9.7
10.8
9.7
9.8
9.3
9.2
9.2
9.4
10.3
9.7
9.2
10
10
10.1
9.5
10.7
10.2
10.3
10.1
9.9
11.3
10.8
9.7
9.7
10
10.3
10.1
65
Jul
Aug
Sep
Oct
Nov
Dec
2006
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
2007
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
2008
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
6.9031
7.1335
8.3381
7.8656
7.8783
7.7406
7.2330
7.2563
7.0082
7.4028
7.7050
7.8409
7.6369
7.2989
7.5230
7.7528
6.2102
6.4554
5.7244
5.1188
5.3864
5.5174
6.4313
6.6051
6.6051
7.2364
7.1125
6.7440
6.5164
6.6528
6.2699
7.0268
6.6726
6.3693
6.1875
6.0685
5.0516
4.8929
3.9034
5.5190
4.5724
5.3934
5.332
4.954
5.310
5.619
6.026
5.881
5.852
5.497
5.619
5.531
5.078
5.490
5.386
5.009
4.992
5.711
5.027
4.338
3.908
3.209
3.160
3.218
3.140
3.489
3.351
3.569
3.831
4.142
5.077
4.258
3.788
3.521
3.708
3.823
4.124
4.126
4.279
4.702
4.289
5.446
6.318
5.728
5.353
5.128
5.382
5.482
5.640
5.588
5.348
5.305
5.025
4.679
4.963
5.255
4.955
4.778
4.685
5.092
4.706
3.924
3.511
3.086
2.962
3.112
3.259
3.644
3.488
3.527
4.208
4.242
4.380
3.588
3.514
3.187
3.224
3.192
3.183
3.337
3.775
4.276
4.194
4.870
5.061
4.178
6.796
5.525
6.493
6.799
6.970
6.088
5.966
5.856
5.837
6.320
5.747
6.024
5.773
5.598
5.357
5.380
4.492
4.344
3.398
3.352
3.081
3.035
3.426
3.355
3.846
3.701
4.261
4.270
3.890
4.159
3.446
3.491
3.501
3.377
3.754
3.703
3.754
3.872
3.650
4.520
3.937
3.754
3.6
3.7
3.7
3.8
3.8
3.9
3.7
3.5
3.8
3.7
3.7
3.7
3.5
3.4
3.4
3.4
3.8
3.2
2.8
2.4
2.3
2.1
2
2
2
2
2.1
2.3
2.1
2.3
2.4
2.1
2.2
2.2
2.2
2.1
2.1
2.1
2.1
2.4
2.4
2.5
10.2
10.1
10.4
10.3
9.7
10.8
10.3
9.6
9.7
9.5
9.7
10.8
10.2
10.4
9.7
9.4
9.2
9
9.5
8.2
8.8
8.5
8.2
8.3
9
9.2
8.9
7.8
8.9
9.1
8.6
8.2
8.5
7.8
8.5
8.5
8.6
9
9.1
9.5
9.4
9.3
4. Thailand
Thailand Monthly Interest Rates
66
BIBOR
Fixed
Deposits 3
Months
Fixed
Deposits
6 Months
Fixed
Deposits
12
Months
Saving
Deposits
Jan
2.40
3.50
3.50
3.75
2.75
8.00
Feb
2.38
3.50
3.50
3.75
2.75
8.00
Mar
2.41
3.50
3.50
3.75
2.75
8.00
Apr
2.33
3.50
3.50
3.75
2.75
8.00
May
2.03
3.50
3.50
3.75
2.75
8.00
Jun
2.00
3.50
3.50
3.75
2.75
8.00
Jul
2.01
3.25
3.25
3.75
2.75
8.00
Aug
2.00
3.25
3.25
3.75
2.75
8.00
Sep
2.01
3.00
3.00
3.50
2.50
7.50
Oct
2.03
3.00
3.00
3.50
2.50
7.50
Nov
2.00
3.00
3.00
3.50
2.50
7.50
Dec
2.00
3.00
3.00
3.50
2.50
7.50
Jan
2.91
3.00
3.00
3.50
2.50
7.50
Feb
2.56
2.50
2.50
3.00
2.00
7.25
Mar
2.46
2.50
2.50
3.00
2.00
7.25
Apr
2.34
2.50
2.50
3.00
2.00
7.25
May
2.30
2.50
2.50
3.00
2.00
7.25
Jun
4.09
2.50
2.50
3.00
2.00
7.25
Jul
3.19
2.50
2.50
3.00
2.00
7.25
Aug
3.04
2.50
2.50
3.00
2.00
7.25
Sep
3.01
2.50
2.50
3.00
2.00
7.25
Oct
2.70
2.50
2.50
3.00
2.00
7.25
Nov
2.72
2.50
2.50
3.00
2.00
7.25
Dec
3.14
2.25
2.25
2.75
1.75
7.00
Jan
2.24
2.25
2.25
2.75
1.75
7.00
Feb
2.19
2.00
2.00
2.50
1.75
7.00
Mar
2.12
2.00
2.00
2.50
1.75
7.00
Apr
2.03
2.00
2.00
2.50
1.75
7.00
May
2.00
2.00
2.00
2.50
1.75
7.00
Jun
2.05
2.00
2.00
2.50
1.75
7.00
Jul
1.89
2.00
2.00
2.50
1.75
7.00
Aug
2.01
2.00
2.00
2.50
1.75
7.00
Sep
1.98
2.00
2.00
2.50
1.75
7.00
Oct
2.01
1.75
1.75
2.00
1.50
6.50
Nov
1.80
1.75
1.75
2.00
1.50
6.50
Dec
1.85
1.75
1.75
2.00
1.50
6.50
Jan
1.73
1.75
1.75
2.00
1.50
6.50
Feb
1.69
1.75
1.75
2.00
1.50
6.50
Mar
1.65
1.50
1.50
1.75
1.25
6.50
Apr
1.72
1.50
1.50
1.75
1.25
6.50
May
1.73
1.50
1.50
1.75
1.25
6.50
Jun
1.73
1.25
1.25
1.25
1.00
5.75
Jul
1.09
1.00
1.00
1.00
0.75
5.50
Aug
1.06
1.00
1.00
1.00
0.75
5.50
Sep
1.10
1.00
1.00
1.00
0.75
5.50
Oct
1.16
1.00
1.00
1.00
0.75
5.50
Nov
1.28
1.00
1.00
1.00
0.75
5.50
Dec
1.30
1.00
1.00
1.00
0.75
5.50
Jan
1.21
1.00
1.00
1.00
0.75
5.50
Period
2000
2001
2002
2003
2004
Prime
Lending
Rate
67
2005
2006
2007
2008
Feb
1.20
1.00
1.00
1.00
0.75
5.50
Mar
1.19
1.00
1.00
1.00
0.75
5.50
Apr
1.13
1.00
1.00
1.00
0.75
5.50
May
0.98
1.00
1.00
1.00
0.75
5.50
Jun
1.09
1.00
1.00
1.00
0.75
5.50
Jul
1.26
1.00
1.00
1.00
0.75
5.50
Aug
1.49
1.00
1.00
1.00
0.75
5.50
Sep
1.73
1.00
1.00
1.00
0.75
5.50
Oct
1.85
1.00
1.00
1.00
0.75
5.50
Nov
2.00
1.00
1.00
1.00
0.75
5.50
Dec
2.24
1.00
1.00
1.00
0.75
5.50
Jan
2.38
1.00
1.00
1.00
0.75
5.50
Feb
2.49
1.00
1.00
1.00
0.75
5.50
Mar
2.58
1.00
1.00
1.00
0.75
5.50
Apr
2.55
1.00
1.00
1.00
0.75
5.50
May
2.59
1.00
1.00
1.00
0.75
5.50
Jun
2.80
1.00
1.00
1.00
0.75
5.50
Jul
2.98
1.00
1.00
1.00
0.75
5.75
Aug
3.17
1.00
1.00
1.25
0.75
5.75
Sep
3.70
1.50
1.75
2.00
0.75
6.00
Oct
3.98
1.75
2.00
2.25
0.75
6.25
Nov
4.06
1.75
2.00
2.25
0.75
6.25
Dec
4.49
2.00
2.25
2.50
0.75
6.50
Jan
4.57
2.50
2.75
3.00
0.75
6.75
Feb
4.68
2.50
2.75
3.00
0.75
6.75
Mar
5.04
3.00
3.25
3.50
0.75
7.25
Apr
5.21
3.25
3.50
4.00
0.75
7.50
May
5.26
3.25
3.50
4.00
0.75
7.50
Jun
5.46
3.25
3.50
4.00
0.75
7.50
Jul
5.42
3.25
3.50
4.00
0.75
7.50
Aug
5.37
3.25
3.50
4.00
0.75
7.50
Sep
5.33
3.25
3.50
4.00
0.75
7.50
Oct
5.26
3.25
3.50
4.00
0.75
7.50
Nov
5.32
3.25
3.50
4.00
0.75
7.50
Dec
5.39
3.25
3.50
4.00
0.75
7.50
Jan
5.21
3.25
3.50
3.75
0.75
7.50
Feb
5.03
3.25
3.50
3.50
0.75
7.50
Mar
4.95
3.25
3.25
3.25
0.75
7.50
Apr
4.54
2.75
2.75
2.75
0.75
7.00
May
4.06
2.25
2.25
2.25
0.75
7.00
Jun
3.93
2.25
2.25
2.25
0.75
7.00
Jul
3.83
2.00
2.00
2.25
0.75
6.85
Aug
3.79
2.00
2.00
2.25
0.75
6.85
Sep
3.88
2.00
2.00
2.25
0.75
6.85
Oct
3.79
2.00
2.00
2.25
0.75
6.85
Nov
3.70
2.00
2.00
2.25
0.75
6.85
Dec
4.17
2.00
2.00
2.25
0.75
6.85
Jan
3.41
2.00
2.00
2.25
0.75
6.85
Feb
3.31
2.00
2.00
2.25
0.75
6.85
Mar
2.93
2.00
2.00
2.25
0.75
6.85
Apr
3.16
2.00
2.00
2.25
0.75
6.85
May
3.16
2.00
2.00
2.25
0.75
6.85
68
Jun
3.26
2.35
2.50
2.75
0.75
7.25
Jul
3.51
2.35
2.50
2.75
0.75
7.25
Aug
3.54
2.35
2.50
2.75
0.75
7.25
Sep
3.60
2.35
2.50
2.75
0.75
7.25
Oct
3.68
2.35
2.50
2.75
0.75
7.25
Nov
3.74
2.35
2.50
2.75
0.75
7.25
Dec
5. Malaysia
Malaysia Monthly Interest Rates
SIBOR 1
Months
Period
2000
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
2001
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
2.79
2.73
2.75
2.73
2.70
2.69
2.72
3.00
3.00
2.97
2.97
3.00
2.98
2.97
2.95
2.96
2.96
2.96
2.92
2.88
2.88
2.91
2.89
2.90
Fixed
Deposits 3
Months
3.31
3.29
3.28
3.26
3.26
3.26
3.26
3.49
3.49
3.49
3.48
3.48
3.47
3.47
3.46
3.45
3.45
3.45
3.45
3.45
3.21
3.21
3.21
3.21
Fixed
Deposits 6
Months
3.44
3.39
3.37
3.34
3.33
3.33
3.33
3.55
3.55
3.55
3.54
3.50
3.52
3.52
3.50
3.49
3.48
3.48
3.48
3.48
3.23
3.22
3.22
3.22
Fixed
Deposits 12
Months
3.94
3.94
3.91
3.91
3.91
3.91
3.90
4.25
4.25
4.25
4.25
4.24
4.24
4.24
4.24
4.24
4.24
4.24
4.24
4.24
4.00
4.00
4.00
4.00
Saving
Deposits
2.70
2.69
2.70
2.69
2.67
2.67
2.69
2.80
2.81
2.84
2.81
2.72
2.69
2.68
2.66
2.68
2.67
2.66
2.60
2.60
2.44
2.33
2.33
2.28
Prime
Lending Rate
6.79
6.79
6.79
6.79
6.75
6.75
6.75
6.76
6.76
6.76
6.76
6.78
6.79
6.79
6.79
6.79
6.79
6.79
6.79
6.79
6.39
6.39
6.39
6.39
69
2002
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
2003
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
2004
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
2005
Jan
Feb
Mar
Apr
May
2.88
2.84
2.85
2.77
2.81
2.83
2.86
2.88
2.88
2.92
2.96
2.98
2.99
2.98
2.99
2.98
2.99
2.99
2.99
2.99
2.99
2.99
2.99
2.99
2.99
2.99
2.98
2.97
2.88
2.81
2.80
2.80
2.79
2.79
2.78
2.77
2.77
2.78
2.76
2.78
2.79
3.21
3.21
3.21
3.21
3.21
3.21
3.20
3.20
3.20
3.20
3.20
3.20
3.20
3.20
3.20
3.20
3.00
3.00
3.00
3.00
3.00
3.00
3.00
3.00
3.00
3.00
3.00
3.00
3.00
3.00
3.00
3.00
3.00
3.00
3.00
3.00
3.00
3.00
3.00
3.00
3.00
3.22
3.22
3.22
3.22
3.22
3.22
3.22
3.22
3.22
3.22
3.22
3.21
3.21
3.21
3.21
3.21
3.01
3.01
3.01
3.01
3.01
3.01
3.01
3.01
3.01
3.01
3.00
3.00
3.00
3.00
3.00
3.00
3.00
3.00
3.00
3.00
3.00
3.00
3.00
3.00
3.00
4.00
4.00
4.00
4.00
4.00
4.00
4.00
4.00
4.00
4.00
4.00
4.00
4.00
4.00
4.00
4.00
3.69
3.70
3.70
3.70
3.70
3.70
3.70
3.70
3.70
3.70
3.70
3.70
3.70
3.70
3.70
3.70
3.70
3.70
3.70
3.70
3.70
3.70
3.70
3.70
3.70
2.30
2.30
2.30
2.30
2.29
2.29
2.25
2.23
2.23
2.22
2.22
2.12
2.10
2.07
2.04
2.04
1.95
1.92
1.92
1.87
1.87
1.87
1.86
1.86
1.83
1.83
1.77
1.77
1.74
1.73
1.72
1.69
1.65
1.64
1.59
1.58
1.60
1.55
1.51
1.50
1.50
6.39
6.39
6.39
6.39
6.39
6.39
6.39
6.39
6.39
6.39
6.39
6.39
6.39
6.39
6.39
6.39
6.00
6.00
6.00
6.00
6.00
6.00
6.00
6.00
6.00
6.00
6.00
6.00
5.98
5.98
5.98
5.98
5.98
5.98
5.98
5.98
5.98
5.98
5.98
5.98
5.98
70
Jun
Jul
Aug
Sep
Oct
Nov
Dec
2006
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
2007
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
2008
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
2.82
2.83
2.84
2.86
2.87
2.89
3.11
3.14
3.14
3.33
3.38
3.73
3.78
3.77
3.69
3.68
3.64
3.60
3.58
3.56
3.55
3.55
3.54
3.54
3.54
3.55
3.54
3.54
3.54
3.54
3.54
3.55
3.55
3.55
3.55
3.56
3.56
3.56
3.56
3.56
3.00
3.00
3.00
3.00
3.00
3.00
3.02
3.03
3.04
3.06
3.12
3.17
3.18
3.19
3.19
3.21
3.21
3.20
3.19
3.15
3.19
3.18
3.18
3.18
3.17
3.15
3.15
3.15
3.15
3.15
3.15
3.15
3.14
3.14
3.14
3.14
3.14
3.14
3.14
3.14
3.00
3.00
3.00
3.00
3.00
3.00
3.04
3.05
3.07
3.11
3.21
3.31
3.32
3.34
3.34
3.36
3.36
3.35
3.34
3.34
3.34
3.34
3.33
3.32
3.32
3.29
3.29
3.29
3.29
3.29
3.29
3.29
3.28
3.28
3.28
3.28
3.28
3.28
3.28
3.28
3.70
3.70
3.70
3.70
3.70
3.70
3.70
3.70
3.70
3.70
3.73
3.76
3.77
3.78
3.77
3.77
3.76
3.75
3.73
3.72
3.71
3.71
3.71
3.71
3.71
3.70
3.70
3.70
3.70
3.70
3.70
3.70
3.70
3.70
3.70
3.70
3.70
3.70
3.70
3.70
1.45
1.44
1.46
1.42
1.40
1.41
1.41
1.42
1.43
1.44
1.46
1.47
1.47
1.46
1.46
1.46
1.46
1.48
1.48
1.49
1.44
1.43
1.44
1.44
1.44
1.44
1.44
1.43
1.43
1.44
1.44
1.44
1.44
1.43
1.42
1.42
1.41
1.41
1.41
1.42
5.98
5.98
5.98
5.98
5.98
5.98
6.20
6.21
6.34
6.47
6.58
6.72
6.72
6.72
6.72
6.72
6.72
6.72
6.72
6.72
6.72
6.72
6.72
6.72
6.72
6.72
6.72
6.72
6.72
6.72
6.72
6.72
6.72
6.72
6.72
6.72
6.72
6.72
6.72
6.72
71