Project Paper Proposal DONE!!!!

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

Project Paper Proposal DONE!!!!

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