Proceedings of Annual Tokyo Business Research Conference
15 - 16 December 2014, Waseda University, Tokyo, japan, ISBN: 978-1-922069-67-2
Factors Affecting Yield Spread of Indonesian Government Bonds
Denominated In Rupiah and U.S. Dollars with Error Correction Model
Approach
Rifqa* and Eko Suwardi**
Government bond is one of the largest contributors to the debt component of the Indonesian’s
government debt. Largest contributor to the government debt comes from the fixed coupon
government bonds denominated in rupiah and U.S. dollar. The yield that fluctuates also cause
fluctuations in the yield spread. If the government can find out the factors that influence changes
in the yield spread, it is expected that the government can determine policies that is related to
debt securities. Furthermore, if the investor can determine the factors that influence changes in
the yield spread, the investor is expected to accurately valuate bond. Research on the factors
affecting the yield spread has not been done in Indonesia, especially those focused on
government bonds. The author uses the Error Correction Model (ECM) in analyzing the BI rate
level, the Credit Default Swap (CDS) Indonesia 10 years, inflation in Indonesia, U.S. inflation,
changes in exchange rate of U.S. dollar against the rupiah, and returns stock market (JCI) as
factors affecting Indonesia's government bond yield spread, both denominated in rupiah and U.S.
dollar. Based on the modeling of ECM, showed that there is cointegration relationship in the
model, so that the balance between variables will occur in the long-term. Simultaneously, these
factors can affect the yield spread between bonds of Indonesia, both denominated in rupiah and
U.S. dollar. Partially, CDS has negative effect on the yield spread Indonesian rupiah-denominated
government bonds, and inflation in Indonesia has positive effect on the yield spread Indonesian
rupiah-denominated government bonds. Furthermore, the Indonesian government bonds
denominated in U.S. dollars obtained results that are parsil, CDS has a positive effect, U.S.
inflation has a negative effect, and changes in the U.S. dollar against the rupiah exchange rate
has a positive effect toward the yield spread of Indonesia U.S. dollars-denominated government
bonds.
Keywords: Yield Spread, Indonesian Rupiah-Denominated Government Bonds, Indonesian
U.S. Dollars-Denominated Government Bonds, Cointegration, ECM.
1. Introduction
Rapid development and integration of global financial market implies the bond market to play
an important role as an alternative source of funding in the current world economic growth
(Ahmad et al., 2009). Investors and governments face difficulties in analyzing the trend of the
government bond market (Chee and Fah, 2013). Although the current Indonesian government
bonds continued to increase, but the causes of changes in the yield spread, difference yield
between two bonds, are unknown.
Increasing government bond ownership, by foreign or domestic investors, will push yields
fluctuations. As the supply and demand equilibrium mechanism, fluctuations in bond yields will
be in line the fluctuation and price then affect the fluctuation in yield spread of Indonesia
government bonds.
__________________________________________________________________________
* Rifqa, is a graduate of Master of Management, Faculty of Economics and Business, Universitas Gadjah Mada.
** Eko suwardi, Ph.D., is an Associate Professor of Accounting at the Department of Accountancy, Faculty of
Economics and Business, Universitas Gadjah Mada.
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Proceedings of Annual Tokyo Business Research Conference
15 - 16 December 2014, Waseda University, Tokyo, japan, ISBN: 978-1-922069-67-2
If the government can find out the factors that influence the changes the government can
determine the refinancing, the issuance of new debt, and also the best maturity of the bonds issued.
Fluctuations in the yield spread can be utilized not only by the government, but also by investors.
Investors can take advantage of fluctuations in the yield spread as a guide in valuing bonds (Ahmad et
al., 2009). Investors should be able to assess when the bonds determine the factors that cause changes in
the yield spread between bonds of Indonesia, both denominated in rupiah and U.S. dollar.
There are several previous studies which analyze the factors that affect the changes in bond yield
spreads, as Fah (2008), Ahmad et al. (2009), Kumar (2012), and Chee and Fah (2013) did. Based on
some of these studies, it was found that there are various factors that affect yield spreads obligations,
such as interest rates, inflation, Credit Default Swaps (CDS), changes in exchange rates, the growth of
gross domestic product (GDP), and the amount of money in circulation. Batten et al. (2006) found that
the rate of growth of the country, inflation rate, interest rate and stock price are the variables that able to
explain the change in the bond yield spread. Furthermore, Chee and Fah (2013) also stated that the risk
of currency fluctuations and risks of inflation are all factors that affect bond yields.
Research about the factors that affecting yield bond spreads have been done before, but most of
these studies conducted outside Indonesia. By contrast, in Indonesia, this research has not been done,
particularly regarding Indonesia's sovereign rating. Therefore, the authors assume that the research on
the factors that influence the Indonesian state bond yield spread is still relevant to do. This study is
expected to be an input for government policy-making relating to the issuance of debt securities as well
as an input for investors in making investment decisions.
Based on the previous study, the author used the interest rate, Indonesian inflation, American
inflation, Credit Default Swaps (CDS) Indonesia in 10 years, changes in the exchange rate of U.S. dollar
against the rupiah and return of the Jakarta Composite Index return (JCI) as the factors that may affect
the yield spread of Indonesian government bonds, denominated in either Rupiah or U.S. dollars. Factors
affecting changes in Indonesia's sovereign yield spread is one of the interesting issues to be studied
because investors use the yield spread as a benchmark in assessing a bond (Ahmad et al., 2009).
2. Literature Review and Hypothesis Development
2.1 Bond and Government Bond
Bringham and Ehrhardt (2005) define bonds as long-term contracts, where the parties require
funds (borrower) agrees to make payments on interest and principal, on specific dates to the party that
issued the bonds. Furthermore, Fabozzi (2007) categorize the bonds as fixed income securities, which
are financial obligations of an entity that promises to pay a certain amount on a certain date in the future.
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Bonds is one of the securities traded on the stock exchanges showed signs of debt securities of issuers
that issued such bonds (Husnan, 2009). Bonds are securities which includes a promise to provide fixed
payments according to a predetermined schedule (Tandelilin, 2010).
Bonds is long-term debt securities issued by governments or companies (Husnan, 2009).
Government is the biggest bond issuer in a country that has the bond market (Fabozzi, 2007). The
Government may issue bonds in domestic currency and foreign currency to be traded in the domestic
bond market. Indonesia is one country that has the bond market, where both the Indonesian government
to issue bonds in domestic currency ie dollars, as well as in foreign currencies like the U.S. dollar and
the yen.
Brealey and Myers (1991) in Husnan (2009) stated that bonds issued by governments often offer
lower rates of return to investors than bonds issued by the company. Contributing factor is the risk borne
by the investor. Investors may feel the risk of bonds issued by the government has a lower risk than
bonds issued by the company.
In Indonesia, government bonds are part of government securities (GS) issued by the Indonesian
government. Government bond issuance has several objectives, namely to finance the budget deficit,
cover the short-term cash shortfalls, and manage the country's debt portfolio. On the other hand, by
issuing government securities government has an obligation to pay interest and principal of the loan with
funds provided in the state budget (Tandelilin, 2010) .
Treasury bonds can be issued with coupons or without coupons. Treasury bond with a coupon
has a periodic payment schedule, ie every three months or six months. While the country without a
coupon bond has no coupon payment schedule and are sold at a discounted price and will pay the loan
principal at maturity (Tandelilin, 2010).
2.2 Yield Spread
Bond yield according Tandelilin (2010) is a measure of revenue bonds that will be accepted by
the investors with tendency of will not be fixed because bond yields are closely linked to the rate of
return required by investors.
Fabozzi (2007) describes yield on bond as composed of two components, namely (1) the yield on
a default-free bonds and (2) a premium over the yield on a default-free bonds that is required to
compensate for the risk associated with the bonds. The risk premium is referred to as the yield spread.
Then, he added a part of the risk premium or yield spread due to default risk called credit spread. If the
credit spread increases, the spread will be larger and the market price of the bond will fall, with
assuming no change in interest rates.
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Proceedings of Annual Tokyo Business Research Conference
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Batten et al. (2006) found that the yield spread is the difference between risky bonds and riskfree bonds. Fah and Ariff (2011) stated that the premium yield spread for investors have liquidity for
securities with different maturities. Furthermore, Boysen-Hogrefe and ABmann (2012) added that the
government bond yield spread is the risk faced by investors when buying government bonds to other
government bonds serves as a benchmark reduction in the yield spread. The yield spread in practice is
widely used by investors as a benchmark in valuing bonds (Ahmad et al., 2009).
2.3 Hypotesis Development
There are several factors that can affect the yield spread between bonds of Indonesia, including
BI Rate, Credit Default Swaps (CDS) of 10 years, inflation in Indonesia, U.S. inflation, exchange rate of
U.S. dollar against Rupiah and Jakarta Composite Index (JCI). These factors are considered to influence
the Indonesian bond yield spread.
H1: BI Rate, Credit Default Swaps (CDS) Indonesia of 10 years, inflation in Indonesia, U.S.
inflation, changes exchange rate of U.S. dollar against the rupiah and return of the Jakarta
Composite Index (JCI) variables simultaneously affect the yield spread of rupiahdenominated of Indonesian government bonds.
H2: BI Rate, Credit Default Swaps (CDS) Indonesia of 10 years, inflation in Indonesia, U.S.
inflation, changes exchange rate of U.S. dollar against the rupiah and return of the Jakarta
Composite Index (JCI) simultaneously affect the yield spread U.S. dollars-denominated of
Indonesian government bonds.
2.3.1
BI Rate
The interest rate is an important economic variable in financial policy. Interest rate is controlled
by the government as one of the efforts in managing monetary policy (and Chee Fah, 2013). In the bond
market, interest rates move in opposite way to bond prices (Fabozzi, 2007). If the interest rate (BI rate)
rises, bond prices will fall and vice versa. Thus, the yield spread will be widened. The increase in bond
yields increase the attractiveness of bonds as an investment so that there is a shift from stock to bond as
the investment with higher return (Prastowo, 2007). Price sensitivity due to changes in the level of BI
rate depends on several aspects (Fabozzi, 2007) i.e the longer the maturity of a bond, the higher the
sensitivity of bond prices to changes in the BI rate, and vice versa.
H3: BI interest rates have a positive effect on bond yield spread.
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2.3.2
Credit Default Swaps (CDS)
Credit Default Swap is a new innovation in the capital markets (Hull, 2004). CDS is the simplest
product to transfer the credit risk of all types of credit derivatives (Fabozzi, 2007). CDS is financial
instruments that can be used by investors to hedge. In the case of government debt, investors use CDS to
express an opinion on the credit worthiness of the government, and to protect themselves in the event of
a default or restructuring government debt (IMF, 2013). CDS is a product that has high liquidity
(Coudert, 2010). Theoretically, the higher the CDS, the higher the default level and it is causing bond
yields to rise. Rising bond yields would cause the yield spread to widen.
H4: CDS has a positive effect on bond yield spread.
2.3.3
Inflation
According to Mankiw (2007), inflation rate is the percentage change in the overall price level
that is highly variable over time between countries. It can be positive or negative, depending on the
degree of inflation itself. Inflation risk or purchasing power risk arising from cash flow impairment
caused by inflation measured in terms of purchasing power. The Fisher Effect (FE) states that the
nominal interest rate is generated by adding two components, namely the real required rate of return
(interest rate will compensate investors for the delay current consumption) and the expected inflation
rate (Shapiro, 2010). Chee and Fah (2013) also stated that inflation risk is risk that cannot be separated
from the bond. Fisher Effect theory also states that countries with high inflation rates will have a higher
interest rate as well. Interest rates will cause bond yields rise, so that the yield spread of bonds of
Indonesia will be widened. Instead, Americans have a lower inflation rate than Indonesia, so it has the
opposite relationship with Indonesia. Inflation is one of the factors that determine changes in bond
yields, where inflation is one form of economic information (Cassola and Porter, 2011). Rising inflation
will trigger a rise in prices of consumer goods in general and it affects investors expected return. In the
bond market, return is expressed in yield so when the yield increases, the bond yield spread will widen.
H5: Indonesia's inflation has a positive effect on bond yield spread.
H6: U.S. Inflation has a negative effect on bond yield spread.
2.3.4
Exchange Rate
Brigham and Ehrhardt (2005) define the exchange rate as the number of units of a given currency
that can be purchased with one unit of another currency. Fabozzi (2007) stated that change in exchange
rate is one of risks faced by investors. Chee and Fah (2013) also stated that investment risk cannot be
separated from bonds. In terms of investors, cash flow from foreign denominated coupon cannot be
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Proceedings of Annual Tokyo Business Research Conference
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certainly known until the coupon is recieved. These cash flows are largely influenced by exchange rate
at the time coupon rate is accepted. Reduction of risk in coupon value in one currency denomination
other than the domestic denomination investment is called exchange rate risk or currency risk (Fabozzi,
2007). Chee and Fah (2013) stated that the risk of exchange rate changes will appear when there is a
change in the price of one currency against another currency, so that foreign investors will receive a
lower return than the domestic investors.
U.S. dollar against the rupiah exchange rate fluctuations has a positive relationship with the level
of interest rates and inflation. If U.S Dollars appreciate, the interest rate and inflation in Indonesia will
increase, so that bond yields will rise. Yield increases will cause the yield spread to widen.
H7: Exchange rate of U.S. dollar against the rupiah has a positive effect on bond yield spread.
2.3.5
Composite Stock Price Index (JCI)
The selection of the type of investments is tailored to the preferences of the investors themselves.
Investors choose to place their funds depending on risks and expected returns. There are three attitudes
of investors toward risk (Husnan, 2009), which is risk averse, risk neutral and risk seekers. If investors
are risk averse then there is tendency of investors to invest in bonds because bonds have a lower risk
with a smaller return. Whereas if investors are categorized as risk seekers, there is tendency of investors
to invest in the stock market because it has a higher risk as well as provide a higher return as well.
Theoretically, the movement of the bond market and the stock market has a relationship in the
opposite direction because they are substitution (Prastowo, 2007). The fall in the price of the bond will
attract investors to invest because the return earned on maturity will be increased, so that the bond
market is more attractive and passionate. Conversely, if the stock returns in this case represented by the
Composite Stock Price Index (JCI) increases, then investors will shift from bonds to invest in the stock
market, so the price of the bond will increase, so that bond yields will decline. Declining bond yields
would cause the yield spread to narrow. Kounitis (2007) in his study also found that the returns of the
S&P 500 index has a negative effect on credit spread changes, in line with the empirical findings of
Collin-Dufresne, Goldstein and Martin (2001).
H8: JCI has a negative effect on bond yield spread.
3. Research Methods
3.1 Population and Sample
The population in this study is all government bonds issued in rupiah and U.S. dollar. While the
sample used in this study were obtained by using the method nonprobability sampling with purposive
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Proceedings of Annual Tokyo Business Research Conference
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sampling method, in which the samples must meet the criteria that have been obtained. Sample of
research determined by purposive sampling based on following criteria:
1. Indonesian government issued bonds denominated in rupiah and U.S. dollar which was published in
2009 and has not matured at the time of the study.
2. Indonesian government bonds which have a maturity of at least 10 years. This criterion is defined as
the longer the maturity of a bond will be more easily influenced by factors variables related to
macroeconomic and market conditions.
3. Bond yield used in calculating the yield spread is the yield of bonds each month obtained from
Bloomberg.
4. Indonesian state bonds used is the fixed rate coupon bonds, plain vanilla (standard bond without
special features) and published in rupiah and U.S. dollar.
After the selection of the sample is in accordance with the criteria, two samples were obtained,
rupiah-denominated government bonds in Indonesia with serial number FR0052 was published in 2009
with a maturity of 21 years and the rupiah-denominated government bonds in Indonesia with serial
number RI190304 published in 2009 with a maturity of 5 years (DJPU, 2013).
3.2 Operational Definition
There are eight variables used in this study, which consists of two dependent variables and six
independent variables.
a. Dependent Variable
The dependent variables are the yield spread of bonds issued in rupiah and yield spread of
government bond denominated in U.S. dollars. The yield spread difference in yield obtained from both
the Indonesian government bonds issued in denominations of U.S. dollar and rupiah-denominated
government bonds with a yield of each country. Government bond yields are used as a reduction factor
is 10-year yield Indonesia Indonesia and the U.S. Treasury for 10 years for America. Yield is published
monthly and is expressed in the 10-year yield (%) by Bloomberg. Yield spreads used in this study is
expressed in decimal form.
b. Independent Variables
Independent variables used in this study are the BI rate (SB), inflation in Indonesia (II), U.S.
inflation (IA), Credit Default Swaps (CDS) Indonesia in 10 years, changes in the exchange rate of U.S.
dollar against rupiah (KR) and return of Jakarta Composite Index (JCI).
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1. Interest rate: the interest rate used is the benchmark interest rate issued by the Government of
Indonesia (BI rate). Interest rates are published every month and expressed in percent (%) by
Bank Indonesia. In this study, the BI rate will be expressed in decimal form.
2. Credit Default Swaps: the level of risk of default Indonesia 10 years issued by Credit Market
Analysis and published every month by Bloomberg. CDS will be expressed in decimal.
3. Inflation: Inflation year on year Indonesia and America are issued every month by each country
and published by Bank Indonesia. Indonesian Inflation and the Americans will be expressed in
decimal form.
4. Changes in exchange rates: the U.S. dollar against the rupiah exchange rate published by Bank
Indonesia every month. Exchange rate changes will be declared as specified in the previous
month. Changes in exchange rates will be expressed in decimal form.
5. Return of Jakarta Composite Index (JCI): the market index used to describe the market
conditions in Indonesia, which is represented by the JCI. JCI will be expressed as a change in the
closing price on a particular month to the previous month. Return JCI further expressed in
decimal form.
3.3 Method of Data Analysis
Analysis of the data in this study used the Error Correction Model (ECM) as a key analytical tool
in performing data processing. Processing the data in the study was conducted by using statistical
software E-Views series 7. Method of Error Correction Model (ECM) was first introduced by Sargan,
but was later popularized by Engle and Granger (1987) to correct an imbalance that can occur between
the variables in the model (Gujarati, 2004). Error Correction Model (ECM) can be obtained through
several stages. First, the data stationarity test on each variable. Second is cointegration test by
establishing a long-term cointegration equation. Third, Error Correction Model (ECM).
3.3.1
Stasionary Tests
To be able to estimate a model of the main steps that should be done is to test the data stationary.
Stationarity can be tested using a formal test known as Unit Root Test. This test is a test that is very
popular is introduced by David Dickey and Wayne Fuller. Unit root test aims to analyze stationary timeseries data (there are no unit roots) or stationary (there is a unit root) (Enders, 2004). The data have a
tendency to approach the stationary average value and fluctuates around its average value (Gujarati,
2004), but in general, the time series data are not stationary. Regressions using stationary data will lead
to spurious regression (characterized by high R2 values and t-stat, F-stat significant but relatively small
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Durbin Watson <0.5). This study uses the Augmented Dickey-Fuller (ADF) test is formulated as
follows.
Or can be written by:
where β1 is the intercept , T is a trend , and α is a constant.
Of the basic model, can be developed into three models (Gujarati, 2004) as follows:
1. Models by incorporating intercept (β1) and trend (T) as the model above.
2. Models by incorporating intercept (β1), namely:
3. The model by incorporating the trend (T), namely:
From the third equation can be formed a hypothesis, namely:
H0: δ = 0; are the roots of the unit (not stationary)
H1: δ < 0; there are no unit root (stationary)
Based on this hypothesis, we will get the conclusion (Gujarati, 2004), namely:
1. If the absolute value of t -statistics of coefficients  (called t-ADF ) is smaller than the Critical
Value McKinnon, meaning there is significant so accept H0 which means there are unit roots. Then it
can be said that the variable is not stationary.
2. If the absolute value of t -statistics of coefficients  (called t-ADF ) is greater than the Critical Value
McKinnon, significant means so reject H0, which means there are no unit roots. Furthermore, it can
be stated that the variable is stationary.
3.3.2
Cointegration Tests
In the previous subsection explained that the regression between non-stationary variables can
lead to spurious regression. One way to anticipate the spurious regression problem is to perform error
correction mdeling. This modeling can be used if there is cointegration between the variables used.
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Cointegration indicates that there is a balance in the long term between the independent variable on the
dependent variable.
For example, if the regression analysis on the independent variable (X) and the dependent
variable (Y) it will form an equation as follows.
If Y and X one or both are not stationary, then u is generally also not stationary. Conversely, if u is
stationary, it can be said that there is cointegration between variables Y and X. Cointegration indicates
that there is a long-term balance between Y and X.
The existence of cointegration indicates that Y and X have a long-term relationship or a longterm equilibrium will be reached. However, it can not be said that in the short term is also a balance
between Y and X. Therefore we need u or may be called equilibrium error to link the behavior of Y in
both the short and long term. Later variable u will be incorporated into the model of short-term Y. This
testing technique called cointegration test residual approach (Gujarati, 2004).
3.3.3
Error Correction Model
If there is cointegration relationship on a linear combination of a bunch of variables, it can be
done, or so-called error correction model with Error Correction Model (ECM). ECM formation can be
done by inserting the equilibrium error (u) which has been obtained previously in the ECM.
In the above equation Y changes allegedly affected by changes in X and the equilibrium error
term (ut-1) or a lag 1 of the regression error term in the long term. If the rate of change of X is equal to
zero, and ut-1 is greater than zero, then the value of Y will be above equilibrium. Therefore the
equilibrium value of the coefficient of error term (β2) is expected to be negative in order to change the Y
will be less than zero and will restore the balance. Value of this coefficient is important to determine the
speed at equilibrium will be reached. The greater the value of β2 (more negative), the faster the process
of adjustment towards the long-term equilibrium. Furthermore, the coefficient β1 indicates the short-term
effect of X on Y and temporary.
4. Results and Discussion
4.1 Indonesian Government Bonds Denominated in Rupiah
In a sample group of Indonesian government bonds that are denominated in rupiah, mixed results
in
testing
stationarity
of
data
were
obtained.
YSRP,
SB,
CDS,
and
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II variables were stationary at first difference, otherwise the IA, KR and JCI variables were at stationary
level. These results indicate that there is a linear combination of stationary variables (level) and
stationary (first difference), so it cannot be concluded that overall variables are stationary with one
degree of integration. Result of stasionarity tests can be seen in Table 4.1.
Table 4.1. Result of Stasionarity Tests
Variables
t-Statistic
YSRP
SB
CDS
II
IA
KR
IHSG
-6.453
-3.528
-10.023
1.083
-4.107
-7.307
-4.728
1%
-2.614
-2.613
-2.613
-2.612
-3.571
-4.153
-4.166
Critical Values
5%
-1.948
-1.948
-1.948
-1.948
-2.922
-3.502
-3.509
10%
-1.612
-1.613
-1.613
-1.613
-2.599
-3.181
-3.184
Degree
First Difference
First Difference
First Difference
First Difference
Level
Level
Level
Therefore, further testing needs to be done to determine whether there is a cointegration
relationship between variables or not. In a sample group of rupiah-denominated showed that there is
cointegration in the model. These results were obtained from the residual probability value of less than 5
% alpha level (prob = 0.000 < 0.05), so H0 is rejected, then there is a stationary equilibrium error in the
variables. Stationary variables indicate that there is cointegration relationship in the model. Result of
cointegration tests can be seen in Table 4.2.
Table 4.2. Result of Cointegration Tests
t-stastisticAugmented Dickey-Fuller
Critical Values:
1% level
5% level
10% level
*MacKinnon (1996) one-sided p-values.
t-Statistic
-4.476
-2.612
-1.948
-1.613
Prob.*
0.000
The next stage is to form ECM. ECM formation is done by regressing equilibrium error obtained
on the long-term cointegration equation together with the other variables used in this study. ECM was
obtained are as follows. Result of ECM can be seen in Table 4.2.
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Table 4.3. Result of Error Correction Model
Variables
C
D(SB)
D(CDS)
D(II)
D(IA)
D(KR)
D(IHSG)
RESID
Adjusted R-squared
F-statistic
Prob (F-statistic)
Coeffisiens
0.000
-0.308
-0.188
0.105
-0.013
-0.015
0.006
-0.582
0.348
4.738
0.001
Prob
0.702
0.089
0.045*
0.035*
0.793
0.239
0.150
0.000*
Remark: * significant at α=5%
In Table 4.3, the error correction coefficient (Resid) has a value and marked according to the
author as negative and less than one in absolute terms. This coefficient is also statistically significant
because the probability is 0.000 (< α = 5 %). The magnitude of the error correction of -0.582 indicates
that the adjustment to the long- term equilibrium yield spreads of 1.718 months (1/0.582 years).
Furthermore, simultaneously, factors such as SB, CDS, II, IA, KR, and JCI are able to affect the
yield spread of rupiah-denominated government bonds. These results were obtained by the F-stasistic
probability value of 0.001 which is less than α = 5 %. These results are consistent with the hypothesis
(H1) which was built by the author. Furthermore, it can be explained that the variable SB, CDS, II, IA,
KR, and JCI may affect the yield spread Indonesian rupiah-denominated government bonds of 34.8 %,
while the rest is influenced by other variables outside the model.
Partially, CDS variable has a negative effect on the yield spread. If the CDS increased by 1 unit,
then the yield spread will be narrowed by 0.188 points. These results are not consistent with the
hypothesis (H4) which states that CDS will be a positive influence on the yield spread. CDS will lead to
an increased probability of default Indonesia. Risk of Indonesian bonds will rise primarily in bonds with
shorter maturity, in this case 10-year government debt. Coudert (2010) stated that the CDS is an
instrument with higher liquidity than bond. CDS are used in this study was 10 years Indonesian CDS,
equivalent to the 10-year government securities used as reduction in determining the amount of the yield
spread of rupiah-denominated government bonds. If the CDS increases, the 10-year yield will rise higher
than the rupiah-denominated government bonds, so that the yield spread will narrow.
II variable has a positive effect on the yield spread. If II increased by 1 unit, then the yield spread
will by 0.105 points. These results are consistent with the hypothesis (H5) determined by the author,
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where the author states that the Indonesian inflation has a positive effect on the yield spread. These
results are also in accordance with the findings of Ahmad et al. (2009) which stated that the consumer
price index has a positive effect on the yield spread. Changes in inflation indicate that the economy is
running. Indonesian Inflation increase is accompanied by an increase in interest rates. As interest rates
increase, the price of bonds will decline as interest rates and bonds have opposite direction (Tandelilin.
2010). Indonesian Inflation increase gives a negative signal to investors, as the risk faced by investors
will rise, so investors will ask for higher yields. The yield on government bonds with a higher maturity
will increase greater than the rate for 10-year yield that is more sensitive to fluctuations in economic
conditions (Bodie et al., 2008). Differences in the increase in the yield on bonds with different maturity
will cause the yield spread to widen. Fabozzi (2007) stated that the Indonesian inflation is inflation risks
faced when investing in bonds.
4.2 Indonesian Government Bonds Denominated in U.S. Dollar
Tests in data stationary were also performed on the sample group of factors that affect the yield
spread of bonds denominated in U.S. dollars. In this test, mixed results on the level of data stationarity
were also found. YSUSD, CDS, KR, and JCI stationary is at level, otherwise the SB, II, and IA variable
is stationary at first difference or level of degree one. Result of stasionarity tests can be seen in Table
4.1.
Table 4.4. Result of Stasionarity Tests of Indonesian Government Bonds Denominated in U.S.
Dollar
Critical Values
Variables
t-Statistic
Degree
1%
5%
10%
YSUSD
-6.123
-3.553
-2.915
-2.595
Level
SB
-4.134
-2.608
-1.947
-1.613
First difference
CDS
-5.538
-3.553
-2.915
-2.595
Level
II
-4.592
-2.608
-1.947
-1.613
First difference
IA
-4.577
-2.608
-1.947
-1.613
First difference
KR
-8.109
-4.131
-3.492
-3.175
Level
IHSG
-5.759
-2.607
-1.947
-1.613
Level
A sample group of rupiah-denominated government bonds showed that there is cointegration in
the model. These results were obtained from the residual probability value of less than 5 % alpha level
(prob = 0.000 < 0.05), so H0 is rejected. then there is a stationary equilibrium error in the variables.
Stationary variables indicate that there is cointegration relationship in the model. Result of cointegration
tests can be seen in Table 4.5.
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Table 4.5. Result of Cointegration Tests of Indonesian Government Bonds Denominated in U.S.
Dollar
t-statisticAugmented Dickey-Fuller
Critical Values:
1% level
5% level
10% level
*MacKinnon (1996) one-sided p-values.
t-Statistic
-4.480
-2.607
-1.947
-1.613
Prob*
0.000
The next stage is to form ECM. ECM formation is done by regressing equilibrium error obtained
on the long -term cointegration equation together with the other variables used in this study. ECM
equation was obtained as follows. ECM was obtained are as follows. Result of ECM can be seen in
Table 4.6.
Table 4.6. Result of Error Correction Model of Indonesian Government Bonds Denominated in
U.S. Dollar
Variables
Coeffisiens
Prob
C
0.000
0.358
D(SB)
0.313
0.247
D(CDS)
1.083
0.000*
D(II)
-0.068
0.311
D(IA)
-0.207
0.014*
D(KR)
0.034
0.026*
D(IHSG)
-0.003
0.703
RESID
-0.529
0.000*
Adjusted R-squared
0.816
F-statistic
30.380
Prob. (F-statistic)
0.000
Remark: * significant at α=5%
In Table 4.6, the error correction coefficient (Resid) has a value and marked according to the
author as negative and less than one in absolute terms. This coefficient is also statistically significant
because the probability is 0.000 (<α= 5 %). The magnitude of the error correction of -0.529 indicates
that the adjustment to the long- term equilibrium yield spreads of 1.718 months (1/0.582 years).
Furthermore, simultaneously, factors such as SB, CDS, II, IA, KR, and JCI together affect the
yield spread between governments bonds denominated in U.S. dollars. These results were obtained by
the F-stasistic probability value of 0.001 which is less than α=5%. These results are consistent with the
hypothesis (H2) built by the author. Furthermore, it can be explained that the SB, CDS, II, IA, KR, and
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Proceedings of Annual Tokyo Business Research Conference
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JCI variables may affect the yield spread of rupiah-denominated government bonds by 81.6 %, while the
rest is influenced by other variables outside the model.
CDS has a positive effect on the yield spread. If the CDS increased by 1 unit, then the yield
spread will widen by 1.083 points. These results are consistent with the hypothesis specified by the
author (H4), where the author states that the CDS will be a positive influence on the yield spread.
Increased CDS will improve Indonesia's credit risk. Increasing the risk will cause investors to demand
higher yields, so that the yield on government bonds denominated in U.S. dollars will increase, whereas
the yield on U.S. T-Bond will not change because it is not affected by changes in CDS Indonesia.
Therefore, the yield spread will be widened. This explanation is supported by the statement of Fabozzi
(2007), which states that the default risk is faced when investing in bonds.
IA variable has a negative effect on the yield spread. If the U.S. inflation rose by 1 unit, then the
yield spread will be narrowed by 0.207 points. These results are consistent with the hypothesis (H6)
determined by the author, where the author states that U.S. inflation would negatively impact yield
spread. These results do not support the findings of this study supported by the principle of Fisher Effect
(Shapiro, 2010). If American inflation increases, while the interest rate is fixed. Indonesia's inflation will
decline. The decline in U.S. inflation will cause cash flow entering Indonesia to increase, so the
purchasing power of consumers will increase. Increased consumer purchasing power resulted in
increased demand for U.S. dollar-denominated bonds. Increased demand will cause the price of the bond
to increase, so that the yield will decrease. U.S. inflation rise will also impact on U.S. T-Bond because
Americans keep strict order for T-Bond yield to remain stable. Level of government bond yields
denominated in U.S. dollar will decline, while the T-Bond is assumed to be fixed, so that the yield
spread will decrease.
Changes in the U.S. dollar against the rupiah exchange rate have a positive effect on the yield
spread. If the U.S. dollar against the rupiah rupiah increased by 1, then the yield will widen by 0.034
points. These results are consistent with the hypothesis (H7) determined by the author, where the author
states that the exchange rate of U.S. dollar against the rupiah has a positive effect on the yield spread.
Results according to research conducted by Chee and Fah (2013) states that the exchange rate has a
positive effect on the yield spread. Batten et al. (2006) stated that the exchange rate is one indicator that
provides macroeconomic uncertainty due to the possibility of a depreciation of the domestic currency
against foreign currencies, thus causing the yield spread to widen. Fabozzi (2007) further states that
bonds are published not in the currency of the country, but in foreign currencies to provide for cash flow
uncertainty in the domestic currency.
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5. Conclusions. Recommendations and References
5.1 Conclusions
Based on the modeling of ECM, there is cointegration relationship in the model, so the balance
between variables will occur in the future. Simultaneously, these factors can affect the yield spread
between bonds of Indonesia, both denominated in rupiah and U.S. dollar. Partially, CDS has a negative
effect on the yield spread of rupiah-denominated government bonds, and inflation in Indonesia has
positive influence on the yield spread of rupiah-denominated government bonds. Furthermore, the
Indonesian government bonds denominated in U.S. dollars showed that the CDS has a positive effect, a
negative effect of inflation America and changes the U.S. dollar against the rupiah exchange rate has a
positive effect on the yield spread between governments bonds denominated in U.S. dollars.
5.2 Limitations
The study of the factors that affect the yield spread between government bonds denominated in
Rupiah or U.S. dollars has some limitations as follows.
1. This research was conducted in the period 2009 to 2013 in monthly, so the number of observations is
not so much. If the research is done daily, the number of observations will be more, so that the test
results are expected to further elucidate the factors that affect the yield spread.
2. This study only uses bonds with fixed coupon with plain vanilla. When the study was conducted
with varying types of bonds, test results can better explain the factors that affect the yield spread.
3. This study uses only six dependent variables of macroeconomic indicators. If the research is done by
more diverse variables, test results can provide maximum results.
5.3 Recommendation
Based on the analysis of the factors affecting the yield spread of government bonds, denominated
either in rupiah and U.S. dollar, then there are several recommendations that can be put forward by the
author.
1. Investors should pay attention to changes in economic conditions, particularly in the Credit Default
Swap (CDS) of 10 year and Indonesian inflation if you want to invest in rupiah-denominated
government bonds. Investors should also pay attention to the changes in the CDS, U.S. inflation, and
changes the exchange rate of U.S. dollar against the rupiah if you want to invest in bonds
denominated in U.S. dollars. The author proposes recommendations because according to the partial
results of testing the factors that affect the yield spread between bonds of Indonesia in this study.
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2. Investors should not panic if there is a change in economic conditions since the change will not
directly impact on Indonesia's sovereign investment. Changes in economic conditions will have an
adjustment to the actual change. This recommendation is proposed by the author as there is balance
that may occur in the future in accordance with the time adjustment.
3. Not only investors, the government should also pay attention to the factors that can affect the yield
spread of government bonds, denominated in either rupiah or U.S. dollars. By considering these
factors, the government can perform policy-making related to the refinancing of debt, the issuance of
new debt and the determination of the coupon rate on the bond.
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