THE INFLUENCE OF MACROECONOMIC FACTORS TOWARD …

THE INFLUENCE OF MACROECONOMIC FACTORS

TOWARD GROSS DOMESTIC PRODUCT OF

INDONESIA FOR PERIOD 1981 – 2015

By:

Morinnalia Isadora

014201300111

A Skripsi presented to the

School of Business President University

in partial fulfillment of the requirements for

Bachelor Degree in Economics Major in Management

December 2016

i

PANEL OF EXAMINERS

APPROVAL SHEET

The Panel of Examiners declare that the skripsi entitled “THE INFLUENCE OF

MACROECONOMIC FACTORS TOWARD GROSS DOMESTIC

PRODUCT OF INDONESIA FOR PERIOD 1981 - 2015” that was submitted

by Morinnalia Isadora majoring in Management from School of Business was

assessed and approved to have passed the Oral Examinations on December 16th

2016.

Dr. Ir. Yunita Ismail Masjud, MSi

Chair – Panel of Examiners

Dr. Dra. Genoveva, MM

Examiner 1

Filda Rahmiati, MBA

Examiner 2

ii

SKRIPSI ADVISER

RECOMMENDATION LETTER

This skripsi entitled “THE INFLUENCE OF MACROECONOMIC

FACTORS TOWARD GROSS DOMESTIC PRODUCT OF INDONESIA

FOR PERIOD 1981 - 2015” prepared and submitted by Morinnalia Isadora in

partial fulfillment of the requirements for the degree of Bachelor in the School of

Business has been reviewed and found to have satisfied the requirement for a

skripsi fit to be examined. I therefore recommend this skripsi for Oral Defense.

Cikarang, Indonesia, December 9th

, 2016

Acknowledged by, Recommended by,

Dr. Dra. Genoveva, MM Filda Rahmiati, MBA

Head of Management Study Program Skripsi Advisor

iii

DECLARATION OF ORIGINALITY

I declare that this skripsi, entitled “THE INFLUENCE OF

MACROECONOMIC FACTORS TOWARD GROSS DOMESTIC

PRODUCT OF INDONESIA FOR PERIOD 1981 - 2015” is, to be the best of

my knowledge and belief, and original piece of work that has not been submitted,

either in a whole or in a part, to another university to obtain a degree.

Cikarang, Indonesia, December 9th

, 2016

Morinnalia Isadora

iv

ABSTRACT

This research examines how macroeconomics influences GDP of Indonesia.

Macroeconomic is important and the relationship with economic growth cannot be

ignored. This research seeks to prove the significance influence of three variables

representing macroeconomic factors which are FDI, Export, and Inflation toward

Gross Domestic Product of Indonesia. This research has 35 observations of time

series for period 1981-2015. Moreover, this research uses quantitative research

with several analysis methods such as Descriptive analysis, Classical Assumption,

Multiple Regression analysis, and Hypotheses testing. Based on the result, FDI,

Export, and Inflation have significance influence toward GDP. Furthermore, the

independent variables simultaneously contribute 90.33% influences toward GDP

while the rest 9.67% is influenced by other factors outside this research.

Keyword: Macroeconomic Factors, FDI, Export, Inflation, GDP

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ACKNOWLEDGEMENT

Through this opportunity, I would like to thank to God who always gave me

blessing and strength to finish this skripsi. Through this opportunity, I would like

to show my gratitude to the following people:

1. Researcher‟s beloved family, especially Mom, Dad, and brother who

always give the unlimited supports, love, blessings and prayers for me.

2. Researcher‟s skripsi advisor, Filda Rahmiati, BBa, MBA. Thank you so

much for the kindness, guidance, attention, and patience. I am so honored

and grateful to have you as skripsi advisor and lecturer.

3. Orlando Santos MBA, Rosita Widjojo, Dr. Dra. Genoveva, MBA, MM,

Marie Ann C, MBA, and the other President University lecturers who have

taught researcher so many knowledge and give so many advices during

these study times. Thank you so much for your care, time, and kindness,

you guys are so cool!

4. My best friends, Rosalia and Vivi Lorensa. Thank you for always being

my caring and supporting friends. You are awesome girls!

5. My comrade, David Willy Otniel, Viona Devi Anbielica, Aris Akbar,

Vivian Noreen, Florencia Irene Chang. Thank you for the crazy time we

shared together through the laugh and struggle.

6. The juniors-like-siblings, Elviny Edison, Joselind Agusta Pratama,

Richard Keane, Ade Dwi Septiani, Gweneal Benita, and others who have

supported and cared. Thank you for your jokes, stories, and craziness.

7. To those who indirectly contributed in this research, your kindness means

a lot. Thank you very much.

8. All of Management students who have shared many experiences through

years in university, I hope we can be impactful person with moral and

value in the future.

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The researcher fully realized that this skripsi is still far for perfection, but always

hope that this skripsi can be helpful for anyone who need it. Researcher hoped this

skripsi can give positive contribution to the readers.

Best Regards,

Morinnalia Isadora

vii

TABLE OF CONTENTS

PANEL OF EXAMINERS APPROVAL SHEET ............................................... i

SKRIPSI ADVISER RECOMMENDATION LETTER ................................... ii

DECLARATION OF ORIGINALITY .............................................................. iii

ABSTRACT .......................................................................................................... iv

ACKNOWLEDGEMENT .................................................................................... v

TABLE OF CONTENTS .................................................................................... vii

LIST OF TABLES ................................................................................................ x

LIST OF FIGURES .............................................................................................. x

LIST OF EQUATIONS ....................................................................................... xi

CHAPTER I ........................................................................................................... 1

1.1. Background ............................................................................................. 1

1.2. Need of the Study .................................................................................... 5

1.3. Problem Identification ........................................................................... 5

1.4. Research Questions ................................................................................ 6

1.5. Research Objectives ............................................................................... 7

1.6. Significance of Study .............................................................................. 7

1.7. Scope & Limitation ................................................................................ 8

1.8. Organization of the Skripsi ................................................................... 8

CHAPTER II ....................................................................................................... 10

2.1. Introduction .......................................................................................... 10

2.2. Gross Domestic Product....................................................................... 10

2.3. FDI .............................................................. Error! Bookmark not defined.

2.4. Exports .................................................................................................. 12

2.5. Inflation ................................................................................................. 13

2.6. Research Gap ........................................................................................ 14

CHAPTER III ..................................................................................................... 16

3.1. Introduction .......................................................................................... 16

3.2. Theoretical Framework ....................................................................... 16

3.3. Hypotheses ............................................................................................ 17

3.4. Operational Definitions of variables ................................................... 18

viii

3.5. Research Instrument ............................................................................ 18

3.6. Sampling ................................................................................................ 19

3.6.1. Population ...................................................................................... 19

3.6.2. Sampling Technique ..................................................................... 19

3.6.3. Sample ............................................................................................ 19

3.6.4. Data Collection Method ................................................................ 20

3.6.5. Data Analysis Method ................................................................... 20

3.6.5.1. Descriptive Statistic Analysis.................................................... 20

3.6.5.2. Stationarity Test ........................................................................ 20

3.6.5.3. Multiple Regression Test .......................................................... 20

3.6.5.4. Classical Assumption Test ........................................................ 21

3.6.5.5. Hypothesis Testing .................................................................... 23

CHAPTER IV ...................................................................................................... 25

4.1. Data Analysis ........................................................................................ 25

4.1.1. Descriptive Statistive Result ......................................................... 25

4.1.2. Normality of the Data ................................................................... 26

4.1.3. Stationarity Test ............................................................................ 27

4.1.4. Multiple Regression Model .......................................................... 27

4.1.5. Classical Assumption .................................................................... 28

4.1.5.1. Normality Test ........................................................................... 28

4.1.5.2. Heteroscedsticity Test ............................................................... 29

4.1.5.3. Multicollinearity Test ................................................................ 30

4.1.5.4. Autocorrelation Test ................................................................. 30

4.2. Hypothesis Testing ............................................................................... 31

4.2.1. T-Test ............................................................................................. 31

4.2.2. F-Test .............................................................................................. 32

4.3. Interpretation of Result ....................................................................... 33

4.3.1. Influence of FDI towards GDP .................................................... 33

4.3.2. Influence of Export towards GDP ............................................... 34

4.3.3. Influence of Inflation towards GDP ............................................ 34

4.3.4. Simultaneous Influence Factors ................................................... 35

CHAPTER V ....................................................................................................... 36

5.1. Conclusion ............................................................................................. 36

ix

5.2. Future Recommendation ..................................................................... 37

5.2.1. For Government ............................................................................ 37

5.2.2. For Future Researcher ................................................................. 38

REFERENCES .................................................................................................... 39

APPENDICES ..................................................................................................... 42

x

LIST OF TABLES

Table 4.1 Descriptive Statistic Result....................................................... 26

Table 4.2 Stationarity Test Result........................................………......... 28

Table 4.3 Multiple Regression Model Result.......……………………….. 28

Table 4.4 Normality Test Result........................…………………………. 30

Table 4.5 Heteroscedasticity Test: Glejser Result...............………….… 30

Table 4.6 Multicollinearity Test Result...................................................... 31

Table 4.7 Durbin-Watson Test Result.....................................………....... 32

Table 4.8 F-Test Result................................................................................ 33

Table 4.9 Coefficient of Determination (R2) Result.................................. 34

Table 4.10 Summary of Analysis.................................................................. 36

LIST OF FIGURES

Figure 1.1 Gross Domestic Product of Indonesia…………………….... 2

Figure 1.2 Gross Domestic Product Growth of Indonesia...................... 3

Figure 1.3 FDI Inflow of Indonesia.....….....…... 4

Figure 1.4 Annual Inflation Rate of Indonesia...............…………........ 5

Figure 3.1 Research Framework ……………………………………...... 17

Figure 4.1 Normality Test of the Data …………………………………. 27

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LIST OF EQUATIONS

Equation 1. Gross Domestic Product …………………………………... 11

Equation 2. Multiple Regression ………………………………...……... 21

Equation 3. Multiple Regression Result……………………………...… 29

1

CHAPTER I

INTRODUCTION

1.1. Background

Indonesia is the fourth most populous country in the world with 257,563,815 as

per 2015 following China, India, and the United States (World Bank, 2016). There

are 13,446 islands in Indonesia‟s territory, make Indonesia archipelago country

(Worldometers, 2016). On the other hand, a report released by World Economic

Forum that Indonesia secures 42nd place out 60 lists in the best country in the

world (Time, 2016). That was achieved from the overall view of economic

situations in the country.

According to Karya & Syamsuddin (2016) Gross Domestic Product (GDP) is the

output that produced in a country by both its people and not, as long as the goods

and services are produced within the country. GDP is the total amount of final

produced goods and services, by the circular flow principle, it is equal to the total

income earned through domestically located production and also equal to total

expenditure on goods and services that domestically produced (DeLong & Olney,

2006).

GDP can be calculated in a certain time period, and usually it is calculated

annually. According to Coyle (2014) GDP is a measurement of nation‟s overall

economic activity and commonly used as indicator of economic health. GDP of

Indonesia is shown in Figure 1.1. The figure shows the GDP of Indonesia is

increasing steadily from 1981, however it fall in 1998 and since 2002 it keep

rising until 2012, starting from 2013 the GDP of Indonesia keep falling until 2015.

2

Figure 1.1 Gross Domestic Product of Indonesia

Source: World Bank, 2016

Nasrullah (2014) stated that economic growth is an important phenomenon of a

country that it will influence the life quality of its people. To develop a country

and its people, a country needs labor, technology, and capital. The educated and

skilled labor is needed to do the job while the equipment and technology is needed

to equip the labor. On the other hand, capital can be received from investment.

Foreign Direct Investment (FDI) brings capital and technology to the host country,

it is important for the developing country to be able to have the access to advance

technology.

According to Simpson (2014), macroeconomic is one of important aspects that

driven the country and the prosperity of the citizens. Asian crisis in 1998 was one

of the worst conditions to the impacted countries such as Indonesia, Thailand, and

South Korea. Indonesia especially suffered from currency crisis, banking crisis,

and debt crisis. According to Bank Indonesia (2016), comparing the other

impacted countries, Indonesia suffered longer and worse because of the unstable

political condition. Followed by financial crisis in 2008 that triggered by America

and impacted to the global economic. As the impact to Indonesia, many foreign

investors disinvest from Indonesia lead to the weakened of Rupiah. Compared to

the other Asia countries such as Malaysia and Singapore, Indonesia was less

0

200.000

400.000

600.000

800.000

1.000.000

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81

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Mill

ion

USD

GDP of Indonesia

Indonesia

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impacted because the value of Export was considered small compared to others

(Bank Indonesia, 2016).

During the crisis in 1998, the value of Indonesian GDP fall sharply from 215.749

billion USD in 1997 to 95.446 billion USD in 1998 as can be seen in Figure 1.1.

Meanwhile, GDP Growth of Indonesia can be seen in Figure 1.2, year 1998

marked to be the greatest fall out of Indonesian history with -13.127 percent GDP

growth. Thailand that suffered from the crisis also reached the bottom with -7.634

percent. Indonesia fall more than Thailand in 1998 and recover slower in the next

year. Thailand was able to recover to 4,572 percent in the next year, while

Indonesia recovered slowly to 0.791 percent in 1999 (World Bank, 2016).

Figure 1.2 Gross Domestic Product Growth of Indonesia


Following crisis in 1998, there was global crisis affected Indonesia at the end of

2008. Domestic currency in 1998 weakened to 9,698.963 from 9,141 in the

previous year, it lead to the fall of export value and Indonesian GDP growth fall to

6.014 percent in 2008 and impacted to the fall to 4.629 percent in 2009, as it is

shown in Figure 1.2. Similar to 1998, the crisis in 2008 brought fall to FDI in

2009, however it recovered quickly. Ever since 2012, Indonesia suffers economic

-15

-10

-5

0

5

10

1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015

Pe

rce

nt

(%)

GDP Growth

Indonesia

4

slowdown caused by global condition such as the increase of interest rate, Greece

economic crisis, depreciation of Chinese Yuan, Greece (Merdeka, 2015).

As the impact of crisis, Indonesian currency weakened greatly, the value of

Indonesian Rupiah against USD was 2,909.380 in 1997 and it skyrocketed to

10,013.623 in 1998 when the Indonesia faced the crisis. A year later in 1999,

Rupiah strengthened to 7,855.150. However Rupiah were fluctuated and have

never gone back to the level of 2,909.380 ever since 1998 (World Bank, 2016).

Moreover, FDI of Indonesia has fallen several times as the impact of crisis. The

crisis in 1998 left Indonesia with -240,800,000 USD of FDI Inflow and in became

worse in the following years. FDI Inflow in 1999 was -1,866,000,000 and in 2000

it fall to -4,550,000,000. The data are shown in Figure 1.3. The unstable political

condition triggered disinvestment in Indonesia, and the value reached minus when

disinvestment is greater than investment (World Bank, 2016).

Figure 1.3 FDI Inflow of Indonesia


As the up and down of a country economic, the live of the people is influenced

(Karya & Syamsuddin, 2016). Inflation Rate can be seen in Figure 1.4.

Indonesia‟s Inflation rate in 1997 was 6.23 percent exploded to 58.387 percent

annually in 1998 and monthly inflation skyrocketed to more than 80 percent in

September 1998, marked Indonesia as a country suffered in Hyperinflation

(Inflation.eu, 2016). Thailand Inflation rate increase slightly from 5.626 percent in

-10.000.000.000

0

10.000.000.000

20.000.000.000

30.000.000.000

US

Do

llar

Foreign Direct Investment Inflow

Indonesia

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1997 to 7.995 percent in 1998 and fall sharply to 0.285 in 1999, ever since then

there were a slight fluctuation. According to Karya & Syamsuddin (2016) the

hyperinflation brought misery to people along with the quality of education fell,

the quality of healthyness fell. From Figure 1.4, can be seen the value of Inflation

is increase from 4.29% in 2012 to to the point of 6.413 in 2013 and it stabel in

±6% for the next couple years, 6.395% in 2014 and 6.363% in 2015.

Figure 1.4 Annual Inflation Rate of Indonesia


1.2. Need of the Study

The need of this research is to examine the influence of Macroeconomic Factors

which are represented by FDI, Export, and Inflation toward Gross Domestic

Product of Indonesia.

1.3. Problem Identification

As shown by Figure 1.4. in the background of study, it is indicated that Indonesia

has an unstable Inflation rate and had suffered from hyperinflation in the 1998. In

-10

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Pe

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(%)

Inflation

Indonesia

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addition to that, Indonesia suffered from Inflation rate of ±600% in 1965 during

30 September Movement (G 30 S-PKI), both hyperinflation in 1998 and 1965

brought Indonesia down in every aspect such as economic, healthiness, education,

and welfare (Karya & Syamsuddin, 2016). Senior Deputy Governor of Bank

Indonesia, Mirza Adityaswara, stated in Tempo (April, 2016) that the inflation

rate of Indonesia is better to be below 4.5%, however the Inflation rate of

Indonesia in the past three years (2013-2015) are ±6%. On the other hand,

Inflation rate influence the price stability.

Ullah & Rauf (2013) stated that there are unceratain performance of

macroeconomic factors, especially in FDI because of the uncertain environment,

in a journal of „Impacts of Macroeconomic Variables on Economic Growth‟ that

used FDI and Export as the independent variables and GDP as the dependent

variable. Furthermore, Ullah & Rauf (2013) stated that there is an impact from

inflation on GDP, high inflation is an indicator that economy of a country is not

controlled properly and is also a reason of negative investment and difficulty of

return on investment. They revealed that FDI, saving rate, and export have

impacts on GDP.

In a journal by Davcev & Hourvouliades (2015), there were several studies about

macoreconomic factors influencing GDP, especially Inflation, they studied the

impact of inflation and interest rate on the GDP. With the problem identified

above, therefore, there is a need to do a research to analyze the influence of

macroeconomic factors towards GDP. Researcher will use FDI, Export, and

Inflation to represent macroeconomic factors.

1.4. Research Questions

Specifically, this study is constructed in order to answer the following question:

1. Is there any significant influence between FDI with GDP of Indonesia?

2. Is there any significant influence between Export with GDP of Indonesia?

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3. Is there any significant influence between Inflation with GDP of

Indonesia?

4. Is there any simultaneously significant influence of FDI, Exchange Rate

and Inflation with GDP of Indonesia?

1.5. Research Objectives

According to the preceding research questions, the research objectives of the

study can be translated as follows:

1. To find out if there is significant influence between FDI with GDP of

Indonesia.

2. To find out if there is significant influence between Export with GDP of

Indonesia.

3. To find out if there is significant influence between Inflation with GDP of

Indonesia.

4. To find out if there is simultaneously significant influence between FDI,

Exchange Rate and Inflation with GDP of Indonesia.

1.6. Significance of Study

Through this research hopefully could expand knowledge, information, and

suggestion for:

1.6.1. Researcher

This research is partial fulfillment of requirement for the researcher to obtain

bachelor degree. However, this research will definitely give valuable experiences

for researcher in conducting a research especially in implementing international

business theories, especially in macroeconomic. In addition from the technical

point of view, researcher will gain knowledge deeply about how to conduct a

research in a right way.

8

1.6.2. Government

The result of this research hopefully could be a contribution or suggestion on

determining the policy of economic development in Indonesia.

1.6.3. The University

The result of research is expected to be useful for academic purpose of President

University students in particular for Management students concentrated in

International Business and it will contribute the literatures and studies in field of

Economic in terms of macroeconomic.

1.6.4. Future Researcher

The result of this research could be used as a baseline for the next research about

macroeconomic of Indonesia, especially in GDP.

1.7. Scope & Limitation

1.7.1. Scope

This research is conducted by analyzing the influence of macroeconomic factors

which is represented by FDI, Export, and Inflation toward GDP of Indonesia.

1.7.2. Limitation

This research focuses on the influence of macroeconomic factors which are FDI,

Export, and Inflation toward GDP of Indonesia for the period of 1981 to 2015.

The country used in this research will be a country part of South East Asia that

had suffered from hyperinflation and the GDP is decreasing in the past few years

which is Indonesia.

1.8. Organization of the Skripsi

This research consists of five chapters, which are Introduction, Literature Review,

Methodology, Data Analysis and Conclusion. Chapter 1 provides the overview of

9

entire research study which contains research background and the need for study

followed by problem statement, research questions and objectives, significance of

the study, limitation and organization of thesis. Chapter 2 provides review of

literature on each variable and research gap. Chapter 3 consists of research

framework, hypotheses, operational definitions, research design and sampling

plan. Chapter 4 consists of descriptive analysis, inferential analysis and

discussions. The last but not least is Chapter 5, which consists of conclusion of

this research.

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CHAPTER II

LITERATURE REVIEW

2.1. Introduction

This chapter is focused not only on both dependent and independent variables, but

how independent variables influence dependent variable and the research gap. The

dependent variable is GDP and independent variables are FDI, Export and

Inflation.

2.2. Gross Domestic Product

Gross Domestic Product (GDP) is the most commonly used to measure output,

income, and the product, also is the total amount of final goods and services

produced according to Delong & Olney (2006). One contribution from Adam

Smith is that he recognized the importance of free trade and labor exchange as a

mechanism of economic growth (Karya & Syamsuddin, 2016). Through „The

Wealth of Nations‟ in 1776, Adam Smith created Gross Domestic Product concept

that countries should be calculated according to their production and commerce,

where the wealth of a country is measured by gold and silver deposit before.

This research uses GDP as the dependent variable because whenever there is an

increase in GDP, it will raise the overall output and it called economic growth

(Ullah and Rauf, 2013). In addition, Abdu (2013) stated that economic growth is

the growth in real terms of GDP in a given year. Economies grow as a result of

several factors, however GDP growth is the most critical because it symbolizes

the output of domestic industries, it creates employment and wealth. GDP is a

measurement of a final value of goods and services produced in a period of time.

The equation of GDP is as follow.

11

𝑮𝑫𝑷 = 𝑪 + 𝑰 + 𝑮 + (𝑿 −𝑴)

Equation 1.

According to DeLong & Olney (2006) the equation is where the C is

Consumption of the country, I is investment, G is Government Expenditure, X is

the value of Export, and M is the value of Import. FDI in this research as the part

of Investment and Export take part in calculating GDP, while Inflation indirectly

influences the GDP through the price level that affecting consumption and

government expenditure.

2.3. Foreign Direct Investment

FDI is the process how residents of a country acquire ownership of assets for the

purpose of controlling the production, distribution, and other activities of a firm in

host country (Moosa, 2002). FDI offers the possibility for resources to developing

countries, becoming an important funds source. Besides, FDI is helpful in

bringing new technologies and funds whereas new technology means an

innovation (Ullah and Rauf, 2013). FDI is an issue that attract attention in

economic over the world. There are two ways of FDI which are inflows and

outflows. FDI Inflows is the value of incoming direct investment made by non-

resident investor in the reporting economy. Meanwhile, FDI Outflows is the value

of outcoming direct investment made by the resident of reporting economy to the

external economies or foreign countries (World Bank, 2016).

Countries starting to participate in joint venture, management, technology

transfer, construction, and manufacturing for the purpose of economic growth

according to Abdu (2013). FDI provides new market, marketing channels, access

to skill and technology, and cheaper production facilities. The developing

countries are able to take advantage from the surplus or profit while the labor are

able to learn new technology. FDI can be classified from the perspective of the

12

investor and host country. According to Elia et al. (2013), types of FDI from the

perspective of investor are as follow:

1. Horizontal FDI

The investor produces the same or similar kinds of goods (in the same industry) in

the host country as in the home country such as Toyota that assembling cars in

both Japan as the home country and Indonesia as the host country.

2. Vertical FDI

The investor invests in different stages in the same industry. There are two types

of Vertical FDI, which are Forward Vertical and Backward Vertical. Backward

Vertical is where the investor moves back towards the raw materials, fulfilling the

role of supplier. Whereas, Forward Vertical is where it takes the investor closer to

the market and acquire the role of distributor such as Toyota acquires car

distributor in Indonesia.

3. Conglomerate FDI

Conglomerate FDI happens when the investor invests in a new unrelated business

with the previous business in host country.

The relationship between FDI and economic growth according to Abdu (2013) is

significantly influenced. In the study, it stated that stability of FDI can stimulate

product diversification through investment into new business. In addition, it

expands business and able to improve employment and raise wages. However,

these benefits are only for some people, such as the employee training limited to

some groups.

2.4. Exports

In macroeconomic theory, a relation between export and economic growth or

GDP is an equation since export is part of national income (Nasrullah, 2014). As a

part of national income, where it is an international trading system that one send

13

goods and services to another country for sale according to the applied conditions.

However, the higher the number of export, the more the country will be sensitive

to the fluctuation in the international market or the world economy (Nasrullah,

2014). Export is influenced by supply and demand of the goods and services.

Demand influences export through the prices, exchange rate, and devaluation

policy. On the other hand, supply influences export through production capacity,

investment, raw material, and deregulation policy.

According to Seyoum (2014) in the book of Export Import Theory, Practices, and

Procedure, international trade played an important role in the economic

development of North America and Australia in the nineteenth century and East

Asian in the twentieth century. While the new prosperity was shared among the

population, East Asia‟s growth leads to increased living standards and reduced

inequality. In addition, Thailand and Malaysia able to reduced poverty from

almost 50% in 1960s to less than 20% by 2000. All of this success is caused by

export, where the government provided the credits, developed export marketing

institutions and restricted competing imports. As the result, the economic grew

about 7 percent per year.

Export of a country is important factor that may affect economic growth.

According to Ullah and Rauf (2013) more exports mean more allocation of

resources and more utilization of resources means more production.

2.5. Inflation

Inflation is understood as an ongoing rise across a broad spectrum of prices.

Meanwhile, an increase in price of one or two goods cannot be described as

inflation unless that increase lead to other goods (Bank Indonesia, 2016).

According to Ullah and Rauf (2013) there are strong arguments that support

inflation as one of macroeconomic factors has effect on economic growth. High

level of inflation is an indicator that shows the economy is not controlled properly

and lead to low growth of economy. Furthermore, According to Kryeziu (2016)

14

inflation is due the fact that it affects the whole population which in modern

economy is done to alleviate the impact of inflationary situations. Inflationary

disorders are wrong economic policies‟ result. Besides, there are three categories

of Inflation:

1. Moderated Inflation

It happens when the overall price level increase slowly and the rate is in single

digit rate. In this state, the monetary system of a country is still functioning well.

2. Fulminant Inflation

It happens when the prices rise by two and three digit rate annually. In this state,

the economic system‟s functions go through serious disorders (Kryeziu, 2016).

3. Hyperinflation

Hyperinflation is a when prices of goods and services skyrocket for more than

50% in a month. Hyperinflation is a high inflation that impacting the price

mechanism to break down. During hyperinflation, people will never sure the true

value of the money and people tend to spend more money before it lose the value

(Delong & Olney, 2006). It rarely happens and usually occurs during war.

Hyperinflation happens in Indonesia during monetary crisis in 1998 whereas

Inflation rate reached 58.387 percent annually, and reached more than 80 percent

monthly (World Bank, 2016).

According to Simpson (2016) Inflation is a key concept in macroeconomic and a

major concern for government, company, and investor. It refers to a broad rise in

price of many goods and services in an economy for a period of time.

2.6. Research Gap

According to Kryeziu (2016), one of macroeconomic factors is Inflation, and

according to Ullah and Rauf (2013) FDI and Export are two of macroeconomic

factors. FDI is used by Yin and Tian (2013) as independent variable for the

research done in China Olusand Enu et al. (2013) done a research in Ghana using

cointegration approach. Furthermore, Olusanya (2013) did a research on FDI

15

Inflow on Economic Growth In a Pre and Post Deregulated Nigeria Economy by

using a granger casuality test. Meanwhile, Ullah and Rauf (2013) use FDI and

Export. In addition, Inflation is used by Kryeziu as one of independent variable on

the research done in Kosovo (2016).

A research by Farid Ullah & Abdur Rauf (2013) “Impacts of Macroeconomic

Variables on Economic Growth” was done using panel data with selected Asian

countries as the sample which are India, Indonesia, Malaysia, Sri-Lanka, and

Pakistan. Furthermore, the independent variables are FDI, Export, Savings, Labor

Force, and Tax Revenue. Ullah and Rauf stated that FDI has positive effect

towards Economic Growth while Exports has negative effect.

A research done by Alush Kryeziu (2016) “The Impact of Macroeconomic

Factors in Economic Growth” conducted in Kosovo by using Public Debt, Budget

Deficit, and Inflation as the independent variables. In addition, it stated that there

is a positive effect of Inflation on Economic Growth. Meanwhile, this research is

conducted with FDI, Export, and Inflation as the independent variables, and GDP

as the dependent variable, with time series data for period 1981 – 2015 in

Indonesia.

16

CHAPTER III

METHODS

3.1. Introduction

This chapter is designed to elaborate the research methodology that used by the

researcher in obtaining necessary information and data for the purpose of this

research. There are two methods to do scientific research; there are qualitative and

quantitative researches. Qualitative research is an inductive method of

reconnoitering the experiences of human being towards social phenomena to

discover the essence of such occurrences and quantitative research is a research

method that involves number and qualification in collecting and analyzing data

(Salvador, 2016). This research is using quantitative method to analyze the data.

3.2. Theoretical Framework

This research focused on The Influence of Macroeconomic Factors on Gross

Domestic Product of Indonesia. In this context, there are four variables in this

study consist of dependent variable that is GDP and independent variables such as

FDI, Export, and Inflation which are representing macroeconomic factors. The

research framework figure can be seen in Figure 3.1.

17

Figure 3.1 Research Framework

Source: Enu et al. (2013), Ullah and Rauf (2013), Davcev & Hourvouliades

(2015)

To support the statement of problem, theories, and opinions are explored.

Moreover, the data collection gathered by researcher from World Bank website.

The researcher will analyze whether there is influences of independents variables

toward dependent variable based on the data. Once the data has its outcome, the

researcher can continue to interpret the results by combining theories, previous

researches, and knowledge of the researcher.

3.3. Hypotheses

In accordance with this research framework that showed above, there are four

variables that will be tested and evaluated with regression analysis. The variables

are FDI (X1), Export (X2), and Inflation (X3) as the independent variables toward

GDP (Y) as dependent variable. Therefore, the research framework has

formulated some hypotheses which will be tested in this research as follow:

H1: There is a significant influence between FDI towards GDP of Indonesia

H2: There is a significant influence between Export towards GDP of Indonesia

FDI (X1)

Export (X2)

Inflation (X3)

GDP (Y)

Simultaneous

Partial

H1

H2

H3

H4

18

H3: There is a significant influence between Inflation towards GDP of

Indonesia

H4: There is a simultaneously significant influence between FDI, Export, and

Inflation toward GDP of Indonesia

3.4. Operational Definitions of variables

The operational definition of the variables is as follows:

FDI (X1): FDI is the process of the source country

resident acquires assets ownership for the

purpose of controlling the production,

distribution, and other activities of a firm in

the host country (Moosa, 2016).

Export (X2): Export is the value of goods and services

provided to the rest of the world (World

Bank, 2016).

Inflation (X3): Inflation is a rise in the prices of goods

common needs that occur continuously and

measured in percent (Muchlas and

Alamsyah, 2015).

Gross Domestic Product (Y): GDP is the value of goods and services

produced within a country by factors of

production (Muchlas and Alamsyah, 2015)

3.5. Research Instrument

Research Instrument is tool that is used to answer the research question. As a

quantitative research that focuses on calculation of data input to obtain the output,

19

the research requires some tools as supportive and generator result in analyzing.

Researcher use software application called SPSS (Statistical Package for Social

Sciences) version 20.0 to process the data and to analyze the statistic result, it is

commonly used to complete research by processing statistical data that help the

analyzing process.

3.6. Sampling

3.6.1. Population

The population for this research is countries that are included in South East Asia

region.

3.6.2. Sampling Technique

This research uses non-probability sampling. It will be used in this research since

the samples do not have known or predetermined chance of being selected as

subjects, with the focus in purposive sampling. Purposive sampling is chosen as

only specific types of sample to provide of information needed. In determining

sampling the researcher gets Indonesia based on criteria and purposes of the

study. These are the following criteria of the sample:

a. The country had suffered from Hyperinflation.

b. The GDP is keep falling in the last three years which are 2013,

2014, and 2015.

3.6.3. Sample

Based on the criteria mentioned above, Indonesia is selected as the sample of this

research as the country has suffered hyperinflation and the GDP is decreasing in

the past three years for the year period of 1981 to 2015.

20

3.6.4. Data Collection Method

As stated in Research Framework, the independent variables in this research are

FDI, Export, and Inflation. This research uses secondary data which data is in

annually timeline and is retrieved from World Bank and previous researches.

3.6.5. Data Analysis Method

3.6.5.1. Descriptive Statistic Analysis

According to Weiss (2012) Descriptive Statistic Analysis summarizes information

of each variable through the calculation of descriptive measures, Mean,

Maximum, Minimum, and Standard Deviation. Maximum is the largest data while

Minimum is the lowest data of observed variables. Moreover, Standard Deviation

is measurement of spread of data around the mean, the smaller the value, the

spread between the highest and the lowest value will be narrow (Schwert, 2010).

3.6.5.2. Stationarity Test

The future statistical characteristic can be forecasted based on the historical data

that occurred in the past (Rosadi, 2012). Stationarity test can be determined by

observing the unit root test of the data. The data has stationarity if the prob. Value

is not greater than the significant of α = 5%. This research uses significance level

of α = 5% or 0.05. Therefore, can be concluded that:

a. If Prob. Value > 0.05, accept null hypothesis (the data has no stationarity)

b. If Prob. Value < 0.05, reject null hypothesis (the data has stationarity)

3.6.5.3. Multiple Regression Test

Multiple Regression is used to forecast dependent variable in the future by

analyzing the empirical data of independent variables towards the dependent

variable in multiple linear regression model and this test shows the influence

between each variables (Santoso, 2013). This research used Multiple Regression

21

Analysis to determine the relationship with dependent variable. The form of

Multiple Regression function is as follow:

𝒀 = 𝜷𝟎 + 𝜷𝟏𝑿𝟏 + 𝜷𝟐𝑿𝟐 + 𝜷𝟑𝑿𝟑 + 𝜺

Equation 2.

Where:

Y : Gross Domestic Product (GDP)

β0 : Constanta

β1-β3 :Regression Coefficient of FDI, Export and Inflation

X1 : FDI

X2 : Export

X3 : Inflation

ε : Random error

According to Gujjarati (2004), it is needed to avoid a deviation of Classical

Assumption Test to avoid problem in Multiple Regression Analysis. Therefore,

the data is processed by conducting Classical Assumption Test which consists of

Normality Test, Heteroscedasticity Test, Multicollinearity Test, and

Autocorrelation Test.

3.6.5.4. Classical Assumption Test

a. Normality Test

Normality test is used to determine whether the dependent and independent

variables that being analyzed is normally distributed (Sugiyono, 2010). Normality

test is done through the graphical analysis or statistic analysis from the analysis

result. Meanwhile, the graphic analysis and statistical analysis is done through the

histogram result and the value of Jarque-Bera Test repectively. The data in

histogram can be determined to be normally distributed if the histogram forms a

22

bell-shape (Winarno, 2011). On the other side, to determine the data is normally

distributed in statistical result, the value of Jarque-Bera should be greater than the

significant level of α = 5% of 0.05, if the value of Jarque-Bera is not greater than

0.05 then the data is not normally distributed.

b. Heteroscedasticity Test

Heteroscedasticity Test tried to analyze whether the multiple regression model has

unequal variance from residual from residual from one observation to another

(Ghozali, 2005). Heteroscedasticity occurs when the dispersion of the error term‟s

probability distribution is not constant while homoscedasticity occurs when the

variance of errors are constant. Good regression model shows no

heteroscedasticity or homoscedasticity (Santoso, 2010). This research has

sgnificant level of α = 5% of 0.05 of significant value, therefore if the probability

value is greater than 0.05 then accept null hypothesis because there is no

heteroscedasticity, if the probability value is no greater than 0.05 then reject null

hypothesis because there is heteroscedasticity.

c. Multicollinearity Test

According to Lind et. al. (2012) stated that multicollinearity exists when

independent variables are correlated. The assumption required the independent

variables have no correlation one another means that if the correlation appeared,

then the multicollinearity problem occurs. The correlation between independent

variables will make the determination of inferences about the correlation among

the independent variables and the individual effect toward the dependent variable.

The method of testing Multicollinearity in regression model is from the value of

VIF (Variance Inflationary and Tolerance). Ghozali (2006) stated if VIF value is

between 0.1 and 10 then there are no multicollinearity between the independent

variables, meanwhile if the VIF value is greater than 10 then there are

multinollinearity between the independent variables.

23

d. Autocorrelation Test

Autocorrelation is the correlation of time series with its own past and future

values (Meko, 2013). A good model regression is when there is no autocorrelation

exists among observations (Santoso, 2013). The Durbin-Watson statistic measures

the autocorrelation in the residuals (Schwert, 2010). The multiple regression

model assumes the research is independent from each other and has neither

positive nor negative autcorrelation (Winarno, 2011). If there is a correlation,

there may be a problem of autocorrelation. According to Santoso (2013), the

basics to decide in autocorrelation test are as follow:

1. If the value of Durbin-Watson < -2 indicates positive autocorrelation.

2. If the value of Durbin-Watson is -2 < Durbin-Watson < 2 indicated

there is no autocorrelation.

3. If the value of Durbin-Watson > 2 indicated negative autocorrelation.

3.6.5.5. Hypothesis Testing

a. T –Test

Coefficient partial correlation analysis (T-Test) is used to find out the partial

influence from the independent variables to the dependent variable. The test is

calculated by comparing the probability value of t-statistics of each independent

variable with the significant level of α = 5%. According to Santoso (2013), if the

probability of t-statistics is greater than 5% or 0.05, then Ho is accepted and Ha is

rejected which means the independent variable has no significant influence

towards the dependent variable. Meanwhile, if the probability t-statistics is less

than 0.05, then Ho is rejected and Ha is accepted which means the independent

variable has significant influence toward the dependent variable.

b. F –Test

Overall Significant Test (F-Test) is applied to determine whether or not all of the

independent variables are simultaneously affecting the dependent variable. The

24

value to determine the simultaneous influence of independent variable towards the

dependent variable can be seen from the value of Prob. F-statistic of the multiple

regression model. According to Schwert (2010), if the p-value is less than 0.05,

then null hypothesis is accepted. The decision to accept or reject null hypothesis

can be concluded through the probability value of f-statistics. According to

Santoso (2010), the basic decisions of F-Test are as follow:

1. If the Prob. of f-statistics > 0.05, Ho is accepted and Ha is rejected

which means that all independent variables have no simultaneously

significant influence towards the dependent variable.

2. If the Prob. of f-statistics < 0.05, Ho is rejected and Ha is accepted

which means that all independent variables have simultaneously

significant influence toward the dependent variable.

c. Coefficient of Determination Analysis (R2)

Coefficient of determination explains how much the independent variables affect

the dependent variable (Winarno, 2011). Coefficient of determination can be

analyzed through the value of R2 if the number of independent variable is less

than two or the value of Adjusted R2

if regression model has more variables.

Coefficient of determination analysis analyzes how big the influence of the

independent variables towards the movement of the dependent variable. The value

of Adjusted R2

should range from 0 to 1.

1. If Adjusted R2

is close to 0, indicated that independent variables have

weak capability to explain dependent variable.

2. If Adjusted R2

is close to 1, indicates that independent variables have

strong capability to explain dependent variable.

25

CHAPTER IV

RESULTS AND DISCUSSION

4.1. Data Analysis

4.1.1. Descriptive Statistive Result

Table 4.1. Descriptive Statistic Result

Source: Processed secondary data

Descriptive statistic provides basic information of the object being researched in

this research, contains the summary of data such as the value of minimum,

maximum, mean, and standard deviation of each variable. Based on the output

above, it shows that:

a. The value of Mean

i. GDP : 3.08E+11

ii. FDI : 5.00E+09

iii. Export : 0.282

iv. Inflation : 0.097

26

b. The value of Standard Deviation

i. GDP : 2.86E+11

ii. FDI : 7.84E+09

iii. Export : 0.064

iv. Inflation : 0.091

c. The value of data processed is 35.

Based on the descriptive analysis result above, it shows the value of mean and

standard deviation of GDP is 3.08E+11 and 2.86E+11 respectively. It can be

estimated that approximately 95% of the values will fall in the range of 3.08E+11

– (1*2.86E+11) to 3.08E+11 + (1*2.86E+11) or between 2.2E+10 and 5.94E+11.

The value of mean is calculated from 1981 to 2015. Meanwhile, standard

deviation value is used to determine how wide the data will spread from minimum

value to the maximum value. Based on the mean and standard deviation, can be

concluded that the spread for GDP is 2.2E+10 to 5.94E+10 means that during the

period of 1981 until 2015, Indonesia maintained the GDP from 2.2E+10 point to

5.94E+11 point.

4.1.2. Normality of the Data

Figure 4.1. Normality Test of the Data


27

This normality test is done with Ms. Excel as the tool to determine the normal

distribution of the data. From the figure above, it can be seen that with the total

data of 35, the data can be said normally distributed.

4.1.3. Stationarity Test

Stationarity Test is done by using Dickey Fuller test as the tool to determine the

stationarity of the data. The variable is categorized to have stationarity if the prob.

value is less than significant level α = 5% or 0.05. All the prob. values in

Augmented Dickey Fuller are less than 0.05 indicates that the variables used in

this research have stationarity.

Table 4.2. Stationarity Test Result


4.1.4. Multiple Regression Model

Table 4.3 Mulptiple Regression Model Result


28

Based on the result above, a regression equation can be constructed by using

number in Coefficient column. Therefore, the equation is constructed as follow:

𝑮𝑫𝑷 = −𝟗.𝟔𝟐𝑬𝟏𝟎 + 𝟑𝟓.𝟓𝟕𝟕𝟑𝟏 𝑭𝑫𝑰 + 𝟏.𝟎𝟏𝑬𝟏𝟐 𝑬𝒙𝒑𝒐𝒓𝒕

− 𝟔.𝟎𝟒𝑬𝟏𝟎 𝑰𝒏𝒇𝒍𝒂𝒕𝒊𝒐𝒏

Equation 3.

The equation can be described as follow:

a. Constanta with the amount of -9.62E+10

It shows that if the value of independent variables FDI, Export, and Inflation

are equal to zero, then the GDP will have the value -9.62E+10

b. Regression Coefficient of FDI = 35.57731

It defines that FDI has influence towards GDP by 35.577731. If FDI

increases by one point and other variables remain constant, GDP will

increase by 35.577731.

c. Regression Coefficient of Export = 1.01E+12

It defines that Export has influence towards GDP by 1.01E+12. If Export

increases by one point and other variables remain constant, GDP will

increase by 1.01E+12.

d. Regression Coefficient of Inflation = -6.04E+10

The negative sign of coefficient number shows that Inflation has negative

influence towards GDP. Thus, if Inflation increases by one point and other

variables are constant, GDP will decrease by -6.04E+10.

4.1.5. Classical Assumption

4.1.5.1. Normality Test

Normality test is used to determine whether the dependent and independent

variables that being analyzed are normally distributed (Sugiyono, 2010). The table

below shows the result of Normality Test through Jarque-Bera value. The Jarque-

29

Bera value will be compared with X2

table with two degrees of freedom under

significant level α = 5%, which is 5.991. Based on the table below, the value of

Jarque-Bera is less than X2

which is 2.478781 < 5.991 and the prob. value is

greater than 0.05 which is 0.289581 > 0.05. As of the result, it can be concluded

that the data have normal distribution.

Table 4.4 Normality Test Result


4.1.5.2. Heteroscedsticity Test

Table 4.5. Heteroscedasticity Test: Glejser Result


Heteroscedasticity test aims to test whether there is disproportion variance of

residuals of one variable to another in regression model. If there is no

heteroscedasticity or there is homoscedasticity, then the regression model is

30

accepted. Heteroscedasticiy test can be seen from the value of Prob. F-statistic.

The table above shows the probability value is greater than the significant level.

Can be concluded that there are heteroscedasticity exists in the model.

4.1.5.3. Multicollinearity Test

Multicollinearity test is done to find out any correlation between one independent

variable and other independent variables in this research. According to Santoso

(2013), multicollinearity issue exists when there is any correlation. A good

regression model should not have correlation between the independent variables.

Table 4.6 Multicollinearity Test Result


To know whether the multicollinearity exists between each independent variable,

it can be seen from the value of Centered Variance Inflation Factors (VIF) of each

variable. The value of Centered VIF should be in the range of 0.1 to 10. Based on

the table above, all values of Centered VIF of each variable are in the range of 0.1

to 10 where the value of FDI‟s Centered VIF is 1.142392, Export‟s Centered VIF

is 2.326990, and Inflation‟s Centered VIF is 2.163947. It means that there is no

multicollinearity between independent variables of the model.

4.1.5.4. Autocorrelation Test

Autocorrelation test is used to analyze whether there is a correlation of error

between t-period and t-1 period in the model. A good regression model is a model

31

without autocorrelation exists. To determine the autocorrelation status, it can be

seen from Durbin-Watson value. The value should be between -2 and 2 to indicate

the model has no autocorrelation.

Table 4.7. Durbin-Watson Test Result

Weighted Statistics

Durbin-Watson stat 1.531826


Based on the table above, the result of Durbin-Watson test shows that the

regression model has no tendency of autocorrelation issue since the value is

1.531826 which is still in the range of -2 to 2. It means that the model has no

autocorrelation.

4.2. Hypothesis Testing

4.2.1. T-Test

T-test is used to know whether there is any significant influence between

independent variables toward dependent variable partially. To determine that the

independent variables have influence toward dependent variable, the value of

Prob. t-statistic should be less than significant level α = 5%. Based on Table 4.3.,

all of three independent variables which are FDI, Export, and Inflation have

partial significant influences toward GDP. The Prob. value of FDI, Export, and

Inflation are 0.0000, 0.0094, and 0.0206, respectively. The Prob. values are less

than significant level α = 5% indicates there is significant influence of each

variable towards dependent variable. The hypotheses of partial test are as follow:

H1: There is a significant influence between FDI towards GDP of Indonesia

H2: There is a significant influence between Export towards GDP of

Indonesia

32


Indonesia

As a result, H1, H2, and H3 are accepted since each independent variable (FDI,

Export, and Inflation) has significant influence towards dependent variable (GDP

of Indonesia).

4.2.2. F-Test

F-Test is conducted to determine the influence of independent variables

simultaneously toward dependent variable of this research. It can be determined

through the value of Prob. F-statistic result based on the calculation model, where

the value of Prob. F-statistic should be less than the significant level α = 5%. The

result is as follow:

Table 4.8. F-Test Result

Weighted Statistics

F-statistic

Prob(F-Statistic)

106.8092

0.000000

Source: Processeed secondary data

The hypothesis of overall significant test is as follow:

H4: There is a simultaneously significant influence between FDI, Export, and

Inflation towards GDP of Indonesia

Based on the table above, the value of Prob F-statistic is 0.000000 less than

significant level of α = 0.05 indicates there is a significant influence. Hence, H4 is

accepted since there is a simultaneous significant influence of FDI, Export, and

Inflation toward GDP of Indonesia.

4.2.3. Coefficient of Determination Analysis (R2)

Coefficient of determination (R2) defines how much the proportion of the

independent variables affect dependent variables (Winarno, 2011). This research

33

uses Adjusted R-squared because there are more than two independent variables.

Coefficient determination is considered good when the value is close to 1.

Table 4.9. Coefficient of Determination (R2) Result


Based on the table above, the value of Adjusted R-squared (R2) is 0.903252. It

indicates that 90.33% of GDP is influenced by variations of three variables which

are FDI, Export, and Inflation, while the rest 9.67% is influenced by other

variables which are not included in this research.

4.3. Interpretation of Result

4.3.1. Influence of FDI towards GDP

Based on multiple regression model result, the coefficient value of FDI towards

GDP of Indonesia is 35.57731, means that an increase by one point of FDI will

lead to increase in GDP by 35.57731. Furthermore, the coefficient value of FDI

towards GDP is 0.0000 which is less than significant level α = 0.05. Hence, can be

concluded that FDI has positive significant influence towards the GDP of

Indonesia.

This result is strengthen with the previous research conducted by Ullah & Rauf

(2013) that result showed that there is a relationship between FDI and GDP.

Indicating that the change in FDI will affect the condition of GDP. Besides FDI

brings advance technology to developing countries along with the knowledges,

trainings that could be conducted to educate employee, and to create job

opportunities. Trade policy in a country from government and international

agreement take part to influence investor to invest in a certain country. To make

34

Indonesia more interesting to invest, government may create more friendly

investment policies and improve infrastructure which is currently being worked

on.

4.3.2. Influence of Export towards GDP

Multiple regression model result shows the coefficient value of Export towards

GDP of Indonesia which is 1.01E+12. It means that every increase of Export by

one point will lead to increase of GDP by 1.01E+12. Moreover, the prob.value of

Export towards GDP is less than 0.05 which is 0.009. Thus, Export is found to be

significant and have positive influence towards GDP. It indicates the change of

Export will affect the level of GDP of Indonesia.

This result is in line with the results from previous research that conducted by

Ullah & Rauf (2013) that Export has significant influence towards GDP. Export is

part of national income besides can bring welfare through employment for the

people. If the value of Export exceeds the value of Import, it will increase the

value of GDP. However, according to World Bank (2016) the value of Net Export

of Indonesia is falling steadily with greater amount of Import than Export in the

past few years, affecting the value of GDP. On the other hand, researcher found

that if a country‟s national income depends too much on Export, a country could

be vulnerable to world economic condition.

4.3.3. Influence of Inflation towards GDP

Coefficient value of Inflation towards GDP as shows in multiple regression model

is -6.04E+11. Meaning to say that every increase of Inflation by one point will

lead to increase of GDP by -6.04E+11. Therefore, can be concluded that Inflation

has negative significant influence towards GDP of Indonesia and the third

hypothesis that states there is a significant influence of Inflation on GDP is

accepted.

Unstable political condition affecting the rapid increase of price in the market or

inflation and it influence the investment. Therefore, the well-maintained and

35

stable inflation will have price stability to ensure people to invest. The findings is

in accordance with result from a research conducted by Davcev & Hourvouliades

(2015) that Inflation has influence on GDP of Romania and Bulgaria.

4.3.4. Simultaneous Influence Factors

Based on the F-test, the significant value in this research is 0.000000. It means

that the independent variables (FDI, Exchange Rate, and Inflation) have high

significance influence level in influencing the dependent variable GDP. In

addition, the value of Adjusted R-square is 0.903252. It shows that the

independent variables that consists of FDI, Exchange Rate, and Inflation influence

the movement of GDP by 90.33% while the rest 9.67% that influence the

movement of GDP can be explained by variables that are not inclueded in this

research. Indicating that macroeconomic variables simultaneously influence the

GDP of Indonesia. Moreover, the intercept in Multiple Regression Model shows

the value of -9.62E+10. The negative estimation of value implies that if the

independent variables are achieving the value of 0, the dependent variable which

is GDP will decreases by -9.62E+10. Based on the intercept value, it means that

the independent variables are affectng the movement of GDP of Indonesia. Hence,

can be concluded that the independent variables that consists of FDI, Export, and

Inflation can affect the movement of GDP of the country.

Table 4.10 Summary of Analysis

R2 0.903252

T-Test

FDI Significant

Export Significant

Inflation Significant

Coefficient β

FDI 35.57731

Export 1.01E+12

Inflation -6.04E+11


36

CHAPTER V

CONCLUSION AND RECOMMENDATION

This chapter defines the conclusions according to the stated scope and limitation

and recommendation for related parties which are government of Indonesia and

future researcher as stated in the significance of the study.

5.1. Conclusion

The objective of this research is to analyze the influence of macroeconomic

factors toward GDP of Indonesia during the year period 1981 – 2015 in annual

basis. This research is conducted wth purposive sampling and time series data

method with a total of 35 observations. This research uses descriptive analysis,

classical assumption test, and hypothesis testing for the analysis. Thus, based on

the analysis which have been done, there are several conclusions that can be

drawn as follow:

From t-test result, the significant influence of each independent variable is

desrcribed as follow:

a. FDI has positive significant influence towards GDP of Indonesia.

H1: There is a significant influence between FDI towards GDP of

Indonesia

Based on the findings, H1 is accepted. The more FDI a country receive,

the more the value of GDP. By keep the stable inflation, keep

improving the infrastructure, have a friendly agreement and clear policy

to make the country interesting to invest.

b. Export has positive significant influence towards GDP of Indonesia.

H2: There is a significant influence between Export towards GDP of

Indonesia

37

Based on the result, H2 is accepted. The more the export of a country

the more it will bring job opportunities and support the country‟s

economic, and to build and maintain relationship with other countries.

Export is influenced by exchange rate, when the money value is high it

may decrease the number of Export.

c. Inflation has negative significant influence towards GDP of Indonesia.


Indonesia

According to the result, H3 is accepted. The change of Inflation rate

will influence the price stability that will influence to consumption level

of people, government expenditure, number of export, and investment.

Unstable and high inflation will affect the price stability and when

people can‟t afford the same amount of goods with the same number of

money, because the value of the money decreases.

5.1.2. From F-Test result, all independent variables which are FDI, Export, and

Inflation are concluded to have significant influence toward GDP of

Indonesia. The significant value of the F-Test is 0.000000, it means that all

independent varables have a high significant level in influencing the GDP

of Indonesia. FDI, Export, and Inflation are influencing the GDP by

90.33% while the remaining 9.67% is influenced by other variables

outside of this research. Indicating that the dependent variable which is

GDP is sensitive of the change in macroeconomic variables

simultaneously.

5.2. Future Recommendation

5.2.1. For Government

Researcher suggests the Government of Indonesia to have the Inflation rate well

maintained at low and stable for as long as possible in order to have price

stability. Price stability will ensure people to invest because the value of money

38

will be stable over time. Besides that, firms and consumers put investment

decision on information from prices. Unstable price level will complicate the

forecast of real return of investment project. In addition to Inflation rate,

researcher suggests the government to focus on Net Export or value of exports

minus imports. When the value of exports exceeds import, the Net Export will be

positive, the positive Net Exports will contribute to the national income, besides it

means more output from the domestic industries, ran by greater number of

employee. It will contribute to economic growth and reduces the number of

unemployment. Moreover, government may try to control the political conditions,

as political condition play a crucial part in the country. Political conditions

impacted the safety and economy of a country directly.

5.2.2. For Future Researcher

For future researcher, the researcher initiates to offer several recommendation and

suggestion for the future research related to the influence of macroeconomic

factors towards GDP. There are several variables that unfortunately are unable to

be used in this research which are labor force, import, savings, tax revenue,

consumer price index, and public debt. In addition, future researcher can analyze

the data monthly if there is supported data in order to gain more accuracy of

research. In addition, future researcher may widen the scope and limitation like

the time period or other samples. The last but not least, researcher suggests future

researcher who interested in economic may be able to examine the influence of

economic growth towards poverty, as it is known that poverty is still a concern for

developing countries.

39

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42

APPENDICES

Appendix 1: Raw Data

Year GDP (USD) FDI (USD) Export (%) Inflation (%)

1981 92,474,000,000 133,000,000 29.040 12.244

1982 94,715,000,000 225,000,000 25.303 9.481

1983 85,369,000,000 292,000,000 26.343 11.787

1984 87,612,000,000 222,000,000 25.587 10.456

1985 87,339,000,000 310,000,000 22.201 4.729

1986 80,061,000,000 258,000,000 19.487 5.827

1987 75,930,000,000 385,000,000 23.934 9.275

1988 88,788,000,000 576,000,000 23.776 8.043

1989 101,455,000,000 682,000,000 24.287 6.418

1990 114,426,000,000 1,093,000,000 25.329 7.813

1991 128,168,000,000 1,482,000,000 25.797 9.416

1992 139,116,000,000 1,777,000,000 27.891 7.526

1993 158,007,000,000 2,004,000,000 26.755 9.688

1994 176,892,000,000 2,109,000,000 26.511 8.518

1995 202,132,000,000 4,346,000,000 26.312 9.432

1996 227,370,000,000 6,194,000,000 25.825 7.968

1997 215,749,000,000 4,677,000,000 27.859 6.230

1998 95,446,000,000 -240,800,000 52.968 58.387

1999 140,001,000,000 -1,866,000,000 35.514 20.489

2000 165,021,000,000 -4,550,000,000 40.977 3.720

2001 160,447,000,000 -2,977,000,000 39.032 11.502

2002 195,661,000,000 145,085,549 32.688 11.879

2003 234,772,000,000 -596,923,828 30.478 6.586

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2004 256,837,000,000 1,896,000,000 32.217 6.244

2005 285,869,000,000 8,336,000,000 34.067 10.452

2006 364,571,000,000 4,914,000,000 31.035 13.109

2007 432,217,000,000 6,928,000,000 29.436 6.407

2008 510,229,000,000 9,318,000,000 29.808 9.777

2009 539,580,000,000 4,877,000,000 24.159 4.814

2010 755,094,000,000 15,292,000,000 24.299 5.133

2011 892,969,000,000 20,565,000,000 26.327 5.357

2012 917,870,000,000 21,201,000,000 24.594 4.280

2013 912,524,000,000 23,282,000,000 23.924 6.413

2014 890,487,000,000 26,277,000,000 23.634 6.395

2015 861,934,000,000 15,508,000,000 21.092 6.363

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