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8/3/2019 Project Paper Proposal DONE!!!!
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The Bivariate Relation of Saving and Investment in Malaysia: A
Cointegration Analysis
CHAPTER 1
INTRODUCTION
1.1IntroductionInvestment and saving both have difference meaning but they have a link to each other
where they will stay dependent. Investment is the one the factor that contribute to the
growth in aggregate wealth. In order to increase investment we need the increase of
aggregate saving and same goes to the individual saving where they will not increase
when the investment does not. It is like a vise versa of a relationship and by reducing
one variable it may affect others. Therefore, investment equal aggregate saving but it is
more suitable to say that aggregate saving is equal to investment.
Malaysian economy has been continue expanding with per capital income rising to
reach prior of the Asian financial crisis in the dynamic environment. This is because
the growth has been supported by the pro-growth policies and development of many
strong banking sector that is able to manage new challenges and obstacles that they are
going to face. Malaysia also can be consider as a high savings country that has the
potential to promote a higher level of consumption without neglecting the prospect for
financing of private investment from domestic sources. We can see the statistic of the
relative important of consumption in economy has been increasing from year 1998 to
2002 which is 56% to 61% of GDP. While, the saving rate has always been remained
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high at 35% of GDP, is just that it has been decline from a peak of 42.4% in 1998( Tan
Sri Dr Zeti Akhtar Aziz).
The sudden boom development of the financial system has given the consumer more
broader selection of financial products and services to them. Therefore they take this
opportunity to make their own decision and think wisely before they make their own
saving and investment. Thus this decision will have lasting implications for their own
financial risk in the future which is based on their own choices. With this financial
planning and management it will forecast the consumption expenses, debts, and saving
of a person at a respective stage.
Nowadays, the rising of the income levels has influence the household sector in
Malaysia to continue accumulate more saving in the bank as to reflect the high
accumulation of deposits against debts. Based on percentage of GDP we can see that
the percentage is 67% which is remains high all the time. Malaysia has a stable
inflation and the cost of financing has been kept low to encourage sustained
consumption and the most important is to stimulate strong investment activities in
Malaysia. When the cost of financing is kept low this will promote smaller
entrepreneur to open their business and this will result in the positive effect in bank
lending.
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1.2Problem Statement1) The direction of the causality of saving and investment, where which variable
affect which one. Is saving cause of more investment or investment cause more
saving in Malaysia.
2) Does the relationship between the saving and investment is vice versa? Does
the increase of 1% of saving may cause increase or decrease of how many
percent of changes in investment?
1.3Research Objective1) To analyze the degree of sensitivity of investment due to the changes in saving.
2) To investigate the long run relationship between investment and saving.
3) To examine the direction of causality between investment and saving.
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1.4Significant of studyThis study is mainly to provide useful and meaningful information which may help
household and investor to add their knowledge and know more details about the study
that has been made and so improve their decision making.
For household this study will show them which way that they can choose to use their
money, through investment or saving.
While to the investor, they can see which one may give them higher return and perhaps
they will choose more toward saving because of the high interest given by the financial
institution which is less risky or investment which is more risky but high return on a
specific period (long term or short term).
1.5Scope of the StudyThe study of this research basically is on the secondary data. The time taken is 41 years
data with the current and latest data that is use which is from 1970 to 2011 based on the
two variables that is use. The data of this research is using the timeline and it is based
on quarterly data.
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1.6Format of the StudyThe format of the study is divided into five major parts which is included introduction,
literature review, data, and methodology, results and conclusion and the
recommendation.
For the Introduction part, it explains briefly regarding the topic of the research, problem
statement, objective, and lastly the scope of the research.
Chapter two which is the Literature Review where this chapter will brief the analysis of
the related literature review. It is very important to have this analysis because the
selected journal will show the relevant theories and concept of the study and also
summarize their findings.
Chapter three is the data and methodology where this part will be discuss on the type of
method, data, research method, theoretical framework, and hypotheses and also the
statistical test use to test the hypothesis where they are suitable or not to be used for the
research and also the ways to get it.
In Results and Finding of the study it will shows where the data is collect and analyst
using a program. Overall it presents a complete account of data analysis and also the
results of the study in a text form, table and figure.
The last chapter which is the Conclusion and Recommendations part where it conclude
overall of the research and some recommendation is also given to make an
improvement based on the data and finding from the analysis that have been made
earlier.
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CHAPTER 2
LITERATURE REVIEW
Some studies have made on the bivariate relation ofSaving and Investment on others
country and they have come out with a conclusion on the relation for the both variable
which has a strong effect on each other. Most of the study mainly concentration on the
causality for both variable where they investigate which variable may influence to the
variable where they may increase or decrease in units change. Some of the study that
have made may have more than two variable in their research but they aim is almost the
same to study the relation of the saving and investment using difference type of
methods that may vary for others research and the results may have a bit significant.
The study made by Sinha.D(2002) on 1948-1999(Yearly data) using Unit root test,
Cointegration test, and Granger Causility and the variable is saving and investment. He
found out that the two Asian countries, namely Japan and Thailand show a long run
relationship between saving and investment rates. By using the structural breaks into
account, they find two variables to have long run relationship for Myanmar and
Thailand. In a short run dynamics of the relationship between the two rates, they
examine the impulse response function. Granger causality test taking structural break
into account for the growth rates of the two variables show that the causality flows from
the growth rates of investment in Malaysia, Singapore, Sri Lanka and Thailand. The
reverse causality is found to hold for Hong Kong, Malaysia, and Singapore.
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Kasuga.H(2004) done a study on the Domestic investment, domestic saving and GDP.
The study is on the OECD countries from 1940 to 1980(Annually data) using the
method Feldstein-Horioka puzzle, estimated coefficient, Vecm and Vars. They found
that clear evidence that countries with developed primary equity markets have larger
saving investment correlations. The results suggest that, if domestic saving increases
net worth ,it increases domestic investment; the impact of domestic saving depends on
financial systems and their development. The influence of financial systems on the
estimation can explain lower savinginvestment correlations in developing countries,
most of which have bank-based and/or relatively inefficient financial sectors. In they
view, the estimated coefficient of saving on investment reflects the effect of net worth
in the presence of domestic capital market imperfections caused by agency problems,
the savinginvestment correlation can be explained by domestic capital market
imperfections, and should not be interpreted as the measure of capital immobility.
Kim Henry.S (2001) using the method Cointegration analysis, Unit root analysis, ADF
test, Philips test and regression coefficient studying on the saving and investment
relation from year 1953 to 2006 based on yearly data. The area of study is at Australia,
Austria, Belgium, Canada, Denmark, Finland, France, Germany, Greece, Ireland, Italy,
Japan, Netherlands, New Zealand, Portugal, Spain, Switzerland, UK and USA. From
his finding he stated that the conventional aggregate shocks cannot fully explain the
high savinginvestment correlation. Even after controlling for productivity, fiscal and
TOT shocks, the saving-retention coefficient remains well above zero. Second, he
confirms the significant role of global shocks in explaining the high savinginvestment
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correlation. The saving-retention coefficients drop more with global shocks than with
domestic shocks in all cases. The saving retention coefficients however remain positive.
Finally, country differences in the size of the GNP and the non-traded sector do not
explain the high saving investment correlation contradicting the simulation results in
Baxter and Crucini (1993) and Tesar (1993). He concludes that the savinginvestment
correlations puzzle remains unsolved. One possible explanation is that cyclical shocks
other than the three shocks considered in this paper are responsible for the continued
high Savinginvestment correlation.
Research by Chakrabarti.A(2006) for the 126 countries using the Multivariate
heterogeneous panel and Cointegration analyses studying on the National saving,
Investment, Balance of payment, Real interest rate, stochastic shocks and GDP from
year 1960 to 2000(Annually data). Over the last three decades, a large and growing
divergence in savings rates across countries has emerged. The gap between the savings
rates of the industrial and developing countries has widened since the mid-1970s, this
divergence is reflected in the growth performance as higher savings rates are associated
with higher income growth. Apart from any direct effect on growth, an adequate supply
of savings should be a central policy objective for economic stability. A national
savings rate that is broadly in line with investment needs reduces the economys
vulnerability to unexpected shifts in international capital flows. In conditions of
increasing international financial integration, high domestic saving contributes to
macroeconomic stability, although it cannot provide full insurance against the
consequences of unsustainable exchange rates or fragile financial systems.
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Singh.T (2008) had study on the Domestic saving and Investment relation using the
Cointegration, Single- equation and System estimator, bi-variate model of Feldstein and
Horioka (1980), unit root test, Granger Causality method in India from 1950-1951 to
2001-2002 on annually data. He found out that the conventional and new CUSUM tests
show the long-run stability of equilibrium residuals and reinforce the cointegrating
relationship between the model series. The long-run slope parameter on saving is
significantly different from zero, but not from one. These results support the FH
hypothesis and suggest the imperfect mobility of capital and home-bias in the asset
portfolio of domestic investors. The stylized evidence showing high savinginvestment
correlations are with consistent the observed behavior of saving and investment. The
heavy reliance of investment on domestic saving also reinforces the `Lucas Puzzle` on
the lack of capital flows from the developed countries to the developing countries with
scare capital and higher marginal product of capital.
Study made by Eslamloueyan.K and Jafari.M (2010) in Mongolia, Bahrain, United
Arab Emirates, Japan, Kuwait, Hong Kong, Singapore, Saudi Arabia, Indonesia,
Tajikistan, South Korea, Sri Lanka, Malaysia, Uzbekistan, China, Oman and Thailand,
Bangladesh, India, Iran, and Pakistan on the domestic saving and investment. They
used the Cointegration, bi-variate model of Feldstein and Horioka (1980), unit root test,
Granger Causality method for a period of 1990- 2006 on annually data. They come out
a with a result that the estimation results suggest that there are long-run equilibrium
relationships between domestic saving and investment in all three groups. Furthermore,
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the estimated short-run coefficients are significant for all groups of Asian countries. The
estimation results indicate that the degree of capital mobility is the lowest for the least
open group. They also observe that the most open group has the lowest speed of
adjustment towards long run equilibrium and hence the highest degree of capital
mobility. In addition, their finding confirms the prediction of modern open economy
macroeconomic theories models that allow the possibility of short-run divergence
between domestic saving and investment. They also find out that more openness to
trade implies greater capital mobility in Asia. Their result confirms the findings of
BahmaniOskooee and Chakrabarti (2005) and Fouquau et al. (2008) regarding the
relationship between trade openness and capital movement. They also note that there is
complimentary relationship between trade in goods and mobility of capital. One policy
implication of this result for the Asian countries is that openness to trade or trade
liberalization can be used as a strategy to attract capital from abroad
Bahmani-Oskooee.M and Chakrabarti.A (2005) had been study on the Saving and
Investment relationship using FeldsteinHorioka puzzle, Savinginvestment correlation
and Panel cointegration for the non-stationary panel of 126 economies study for a
period from 19602000 on annually data. The study uses recently developed techniques
of heterogeneous panel cointegration in examining if national saving and investment
exhibit any long run relationship. There is a significant and robust positive relationship
between the ratio of gross domestic investment to GDP and the ratio of gross domestic
saving to GDP. The evidence provides strong support for a systematic effect of
country-size and openness on the saving investment relationship: the
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relationship is significantly stronger among the group of high-income countries than it
is for the group of low-income countries and among the group of closed economies than
it is for the group of economies that were open after initial closure.
Kim.S, Sunghyun H. and Wang.Y(2007) had studied on saving and investment
relationship using the method of Savinginvestment correlation, FeldsteinHorioka
puzzle and Capital mobility at the countries of China, Hong Kong, Indonesia, Japan,
Korea, Malaysia, Philippines, Singapore, Taiwan, and Thailand from a period of 1980
to 2002(annually). In this paper, we have explored the SI correlation of East Asian
countries in relation to international capital mobility. Generally, the direction of
changes in the SI correlation over time is consistent with the changes in the degree of
capital mobility. The SI correlation decreases as capital mobility increases over time.
Additionally, the S I correlation in East Asia is always less than that in the OECD
countries in all periods. This is consistent with the fact that capital mobility in East Asia
is lower than that among the OECD countries. On the other hand, even after controlling
cyclical shocks, the SI correlation remains positive, which may imply that the absolute
degree of capital mobility is still low. Despite these findings, it is difficult to directly
infer the degree of capital mobility of individual countries because the SI correlation
varies greatly across countries in a country specific analysis. This cross-country may
reflect either the presence of other country specific factors that are not considered in this
paper or the small sample size. Therefore, theS I correlation may provide indirect
evidence of a governments stance on the current account policy, whether governments
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target the current account balance as their policy goal or simply allow for the current
account as a residual of economic activity.
The study made by Evans.P, Kim Bong.H and Oh Keun.Y (2008) also on the Saving
and Investment relation using the FeldsteinHorioka puzzle, Saving-retention
coefficients, Capital mobility, Time-varying and coefficients on Argentina, Austria,
Canada, Italy, Japan, Sweden, United Kingdom and United States for a period of 1973-
2003 annually data. This study conclude that by estimates FeldsteinHorioka saving-
retention coefficients by using methods that allow domestic saving and investment rates
to be cointegrated and the saving-retention coefficient to vary over time. The changes in
the saving-retention coefficients indicate how international capital mobility has changed.
They obtained the following empirical findings. First, the parameter stability of saving-
retention coefficient is strongly rejected. Second, capital mobility from Canada to the
rest of the world appears to have long been perfect: its path for domestic investment is
basically disconnected from its path for domestic saving. The result that cointegration is
rejected for Canada does not indicate that Canada violates her long-run budget
constraint, however. When they apply a unit-root test that permits nonlinear mean
reversion in the ratio of its current-account surplus to its GDP, they find evidence of
nonlinear mean reversion. Nonlinear mean reversion implies that the Canadas long-run
budget constraint is indeed satisfied. Third, at the turn of the 20th century, capital
appears to have been much more mobile between both Japan and the United Kingdom
and the rest of world than it has been in the postwar period. Fourth, capital appears
never to have been especially mobile between the United States and the rest of the
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world. Fifth, the capital mobility into and out of Argentina, Italy and Sweden has risen
since around 1970. Finally, the capital mobility of the countries that we consider
appears not to have increased monotonically in the postwar period. Our findings
therefore confirm those of Taylor (1996).
Amir Khalkhali.S , Dar.A, and AmirKhalkhali.S (2003) study on the government size
(GS), investment (IY), saving (SP), current account (CA), government financial balance
(SG) and the growth rate of government consumption (GC) relation b using the
FeldsteinHorioka puzzle, Saving-retention coefficients and Savinginvestment
correlation method for the 19 OECD countries Australia, Austria, Belgium, Canada,
Finland, France, Germany, Greece, Iceland, Ireland, Italy, Japan, Netherlands, Norway,
Portugal, Spain, Sweden, the United Kingdom and the United for a period of 1971
1999(annually). They examined the savinginvestment-deficit relationship within the
context of a random coefficients model that permits the parameters to vary over time.
Their period-specific results strongly support the crowding-out effect as well as the low
capital mobility argument implied by the FB model for the countries as a whole.
However, the strength of the crowding-out effect appears to weaken, and the degree of
capital mobility appears to increase in the 1990s as compared to the 1970s and 1980s.
They specific results show that the crowding out effect is generally weaker, and the
degree of capital mobility generally higher for country groups with the larger
governments. However, the differences appear to be most significant when we compare
the country group with the largest government with all other country groups, with those
differences being much more modest among the latter. Overall, our period-wise and
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group-wise results indicate low capital mobility and crowding out for OECD countries
as a whole. Yet, significant differences in the country specific results suggest that it is
misleading to draw conclusions about crowding out and capital mobility for specific
countries from the period-wise or group-wise results.
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CHAPTER 3
DATA AND METHODOLOGY
3.1 Introduction
This topic mainly list out all the details about the data and methodology which has been
used in this research. For the data part, there is a clear explanation on the steps to
collect data and where it is obtain and next the data is test and analyst. In Methodology
part in an elaboration on the types of methods or test that is used to be performed in the
research.
3.2 Data
Data which used in this research is secondary data where there is two variables which
are Investment and Saving. It is also a time series data of 41 years from 1970 until
2011 on a quarterly basis. This quarterly data is very important for the study because
this will determine the long run relationship between Investment and Saving.
3.2.1 Source of Data
All the sources of the data for the research were obtained from the Bank Negara
Malaysia Library andS
tatistical Department of Malaysia.
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3.2.2 Descriptive Data blank
3.2.2.1 Determinants of Variables
There is only two types of variables which contributes in this research which is the
dependent variable and the independents variable. Dependent variable is the variable
that is to predict or to estimate while the independent variable is a variable that will
provides the basis for estimation.
3.2.2.1.1 Dependent Variable
In this research, the Investment will be the dependent variable.
3.2.2.1.2 Independent Variable
For the Independent variable the variable will be the saving.
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3.2.2.2 Relationship table used for variable selected
The relationship involves the dependent variable as Investment from the independent
variables which is Saving. This process is roughly to see the relationship between
investment and saving in Malaysia.
Independent Variable Dependent variable
InvestmentSaving
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3.3 METHODOLOGY
Statistical measure or Regression is a that attempts to determine the strength of
the relationship between one dependent variable usually denoted by Y and a series of
other changing variables known as independent variable. The two basic types of
regression are linear regression and multiple regression. Linear regression uses one
independent variable to explain and/or predict the outcome of Y, while multiple
regressions use two or more independent variables to predict the outcome. The general
form of each type of regression is:
Linear Regression: Y = a + bX + u
Multiple Regression: Y = a + b1X1+
b2X2 + B3X3 + ... + BtXt + u
Where:
Y= the variable that we are trying to predict
X= the variable that we are using to predict Y
a= the intercept
b= the slope
u= the regression residual.
In multiple regressions the separate variables are differentiated by using subscripted
numbers. Regression takes a group of random variables, thought to be predicting Y, and
tries to find a mathematical relationship between them. This relationship is typically in
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the form of a straight line (linear regression) that best approaches all the individual data
points.
3.3.1 STATISTICAL PACKAGE FOR SOCIAL SCIENCE (SPSS)
SPSS (SPSS 16.0) is a computer application that provides statistical analysis of data. It
allows for in-depth data access and preparation, analytical reporting, graphics and
modeling. SPSS (stands forStatistical Package for the Social Sciences) Text Analysis
for my surveys is an ideal tool for categorizing analyze that the information obtained
from them can be integrated with the rest of the quantitative survey data. This method
can used to dependent variable (DV provide more descriptive statistics, including the
variance, mean, Skewness, Kurtosis, the median, percentage and other descriptive
statistics and information for variable.
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3.3.1.1 MULTIPLE REGRESSION
A regression equation expresses the linear relationship between two or more variables.
In the regression analysis, the) and the independent variables (IVs) have to identify and
these are usually based on a theoretical basis. The formula that will be use is:
Y = Dependent variable
Bo = Constant Value
B1, = Regression coefficients
X = Independent variable
= Residual term
So, below is the equation that is use for the regression analysis as follow:
Log Investment = dependent variable
0 = constant value
1 = Regression coefficient
Saving = Independent variable
Y= 0 + 1X1 +
Log Investment= 0
+ 1Log Saving
t+
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= Residual term
3.4 THE HYPOTHESIS
Hypothesis can be divided into two types:
y The null hypothesis (Ho)
The null hypothesis is a hypothesis about a population parameter. The purpose
of hypothesis testing is to test the viability of the null hypothesis in the light of
experimental data. Depending on the data, the null hypothesis either will or will
not be rejected as a viable possibility.
y The alternative hypothesis (H1, H2, H3,..Hx)
The alternative hypothesis is put forward. If the data are sufficiently strong to
reject the null hypothesis, then the null hypothesis is rejected in favor of an
alternative hypothesis.
3.5 EXPECTED OUTCOME
In this study the expected outcome is to examine the causality between the relationship
of saving and saving. This study also will determine whether the sensitivity is on
saving or investment more. In order to see the sensitivity to change between the both
variable we also look on their relationship in long run relationship.
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HYPOTHESIS 1:
Ho1: There are no changes in the independent variables (Saving) towards the sensitivity
on Investment.
Ha1: There are changes in the independent variables (Saving) towards the sensitivity
on Investment.
HYPOTHESIS 2:
Ho2: There is no co-integration relationship of independent variables (Saving) on
Investment.
Ha2: There is a co-integration relationship of independent variables (Saving) on
Investment.
HYPOTHESIS 3:
Ho3: There is no impact on Investment based on the independent variables (Saving)
Ha3: There is positive impact on Investment based on the independent variables
(Saving)
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GANTT CHART
TASK/WEEK 1 2 3 4 5 6 7 8 9 10 11 12 13
Submission of RT
RT approval
Literature Review
Data and Methodology
Proposal Submission
Data collection and data entry
Analysis
Finding and conclusion
Review with advisor
Project paper submission
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REFERENCES
AmirKhalkhali.S , Dar.A, and AmirKhalkhali.S (2003) Savinginvestment correlations,
capital mobility and crowding out: some further results. Economic Modelling 20 (2003)11371149
Bahmani-Oskooee.M and Chakrabarti.A (2005) Openness, size, and the saving
investment relationship Economic Systems 29 (2005) 283293
Chakrabarti.A (2006) The savinginvestment relationship revisited: New evidence frommultivariate heterogeneous panel cointegration analyses. ScienceDirect, p: 402-419
Eslamloueyan.k and Jafari.m (2010) Capital mobility, openness, and saving-investment
relationship in Asia Economic Systems 29 (2005) P: 283293
Evans.P, Kim.B-Han, Oh.K.Y 2008. Capital mobility in saving and investment: A time-varying coefficients approach. Journal of International Money and Finance 27 (2008)
806815 Kasuga.H 2004 Savinginvestment correlations in developing countries. Economics
Letters 83 P: 371376
Kaya.H Saving Investment Association in Turkey Department of Economics, Bahcesehir
University Curagna Cad. Besiktas/ Istanbul, Turkey
Kim Henry.S (2001) The savinginvestment correlation puzzle is still a puzzle. Journalof International Money and Finance. P: 1017-1034
Kim.S, Sunghyun H. and Wang.Y(2007) Saving, investment and international capitalmobility in East Asia. Japan and the World Economy. ScienceDirect P: 279- 291
Sinha.D (2002) Saving- investment relationships for Japan and other Asian countries.
ScienceDirect, p: 1-23
Singh.T (2008) Testing the Saving-Investment correlations in India: An evidence from
single-equation and system estimators. ScienceDirect, p: 1064 - 1079