An Emprical Analysis on the Determinants of FDI in the PH - Template

UNIVERSITY OF SANTO TOMAS FACULTY OF ARTS AND LETTERS

An Empirical Analysis on the Determinants of Foreign Direct Investments in

the Philippines

A Thesis presented to the

Faculty of Arts and Letters

University of Santo Tomas

In Partial Fulfilment of the

Requirement for the

Bachelor of Arts Major in Economics

By:

Montero, Paul Gian I.

Ramos, Mary Louise M.

February 2014

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ACKNOWLEDGEMENT

The researchers would like to thank first and foremost God, for guiding us

through this statistical journey; to our thesis adviser Dr. Carlos L. Manapat; to

our defense panel, Dr. Alvin P. Ang and Dr. Emmanuel Lopez for guiding us

through the necessary changes of our thesis paper, and to our supportive family

and friends who never fail to encourage us to move forward.

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ABSTRACT

Most developing countries consider foreign direct investment (FDI) as a vital

source of satiating the resource gaps that hinder their economy’s development.

This brings them to improve or develop their country’s assets in order to attract

investments. The Philippines is not an exception in having this goal of

encouraging FDI, but there are issues regarding four of the country’s resources

that are used in the study: the unsteady spending for infrastructure development,

the annual increase of the country’s population, the instability and volatility of

both interest rates and total custom duties. All of these four factors were examined

as indicators of foreign direct investments, and if they each have a significant

relationship with FDI. The first part of the paper provides an in-depth discussion

of the issues, followed by theories and supporting studies. The second part is

about empirical findings and results, to which the researchers used linear

regression analysis in order to find the relationships using data from 1990-2012,

duration of 23 years. The empirical findings are: (i) infrastructure spending is

statistically insignificant and directly related to FDI inflows; (ii) interest rate is

statistically insignificant and negatively related to FDI inflows; (iii) total custom

duties collected is statistically significant and negatively related to FDI inflows;

and (iv) population is statistically significant and directly related to FDI inflows.

Keywords: Increasing Foreign Investments, Infrastructure Spending,

Population, Interest Rate Volatility, Total Customs Duties Collected, Horizontal

and Vertical FDI, Public Goods

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Table of ContentsCHAPTER 1: INTRODUCTION.............................................................................................6

Background of the Study......................................................................................................6

Theoretical Framework.........................................................................................................8

Conceptual Framework.......................................................................................................11

Scope and Limitations........................................................................................................14

Significance of the Study....................................................................................................14

Definition of Terms............................................................................................................15

CHAPTER 2: REVIEW OF RELATED LITERATURE...................................................19

CHAPTER 3: METHODOLOGY..........................................................................................27

3.1 Overview.......................................................................................................................27

3.2 Research Design...........................................................................................................27

3.3 Data Gathering Procedures...........................................................................................28

3.3.1 Secondary Data Collection....................................................................................28

3.4 Treatment of Data.........................................................................................................29

CHAPTER 4: DATA PRESENTATION AND ANALYSIS.................................................34

Data Results and Analysis..................................................................................................34

CHAPTER 5: SUMMARY, CONCLUSIONS, RECOMMENDATION..............................43

APPENDIX A.........................................................................................................................47

Figure 1: Linear Regression of FDI and Infrastructure Spending......................................47

Figure 2: Linear Regression of FDI and Interest Rate........................................................48

Figure 3: Linear Regression of FDI and Total Customs Duties.........................................49

Figure 4: Linear Regression of FDI and Population...........................................................50

Figure 5: Mulitple Regressions (Original Data).................................................................51

Figure 6: Multicollinearity Test..........................................................................................52

Figure 7: Heteroskedasticity ESS1.....................................................................................53

Figure 8: Heteroskedasticity ESS2.....................................................................................54

Figure 9: Autocorrelation Test............................................................................................55

APPENDIX B.........................................................................................................................56

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Table 1. Data of Dependent Variable: Foreign Direct Investment.....................................56

Table 2. Data of Independent Variable: Infrastructure Spending.......................................57

Table 3. Data of Independent Variable: Interest Rate........................................................58

Table 4. Data of Independent Variable: Total Customs Duties..........................................59

Table 5. Data of Independent Variable: Population...........................................................60

Table 6. Multiple Regression Data (Original)....................................................................61

Table 7. Multiple Regression Data (Transformed).............................................................62

Table 8. Heteroskedasticity Data (Arranged).....................................................................63

Bibliography...........................................................................................................................64

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CHAPTER 1: INTRODUCTION

Background of the Study

It is recognized worldwide that growing inflows of foreign direct

investments can provide potential benefits and promotion of the economic

development of the host countries. In Asia alone, there is an ongoing competition

for FDI, as each economy strives to make their markets attractive for investors.

Although the region is seen to be attractive as a whole, developing countries still

try to increase inflows in their own territorial boundaries. China and Japan

dominate the FDI share in the region, followed by Singapore and Hong Kong. In

the years 2011-2012, Cambodia and Myanmar has overtaken the Philippines in

shares of FDI which provides a problem for the Philippine archipelago. This is the

kind of issue that the study aims to understand and provide a deeper analysis.

The Philippines has been open in welcoming investors in the country; with

their competitive labor workforce achieving a high education priority, a literacy

rate of 94.6%, and the flexibility of the Filipinos in speaking the universal

language. With the country’s wealth of natural resources, foreign businessmen

have always considered placing their money and make good business in the Asian

archipelago. But in spite of all these given qualities of the country, it is still of

question as to why the Philippines is being left behind in terms of foreign direct

investments. The country is increasingly facing competition from other FDI hosts

in the region including those from newly emerging markets. There is need for

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continuous adjustments as all countries simultaneously outcompete each other to

attract limited FDI resources. With the limitations that now beset incentives

(which tend to be matched by a second country each time one country enacts

one), host countries will offer investment regimes that are dynamic and constantly

moving (Chia and Freeman, 1999). Research was done to see what’s making the

other Asian countries grab more investments, and among these studies, four

common factors were found. First is infrastructure, investors see a country with

many stable building structures and ports (both aerial and marine) is a good area

for investments. This can be seen in the amount the government spends for

infrastructure development. Many available ports, buildings and accessible roads

would create more chances of FDI increase since they imply a convenience in

transportation. (OECD, 2000) In the Philippines, however, the amount of

infrastructure spending does not provide a steady annual increase despite the

country’s necessity.

The second factor is population. A high number of the country’s

population means a high number of consumers for any commodities a foreign

company may provide. Investors compare population as an indication of market

size and consider the countries with bigger numbers of residents. (Khan & Nawaz,

2010) It is only of question if the Philippines’ annual increase in population

would be significant in diverting the investors’ attention away from lesser

populated countries. Countries like China, Indonesia and Japan have greater

population than the Philippines, and at the same time attract higher numbers of

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foreign direct investment inflows. This trend of whether or not a high population

automatically implies high investments would be discussed. Third factor is total

customs duties collected in a year. Customs duties are taxes collected from

imports sent to the country. Customs duties are used to represent the amount of

imports and levels of tax rates in this study. Investors, being profit-oriented

individuals, are more inclined to invest in countries with lower taxes need to be

collected as high taxes would mean a decrease in their total profits. Lastly, the

interest rate is also a common factor that makes an investor decide whether or not

to place his money on the country. Interest rate is a measure of the cost of the

capital. A higher interest rate implies more costly investment and, therefore, more

likely to defer FDI.

Theoretical Framework

There are many theories that attempt to explain the determinants of FDI.

These theories are significant steps towards the development of a systematic

framework for the emergence of FDI. In this study, the researchers will

incorporate macroeconomic theories that will aid in supporting the thesis. These

will be used to assess the behaviour of foreign investment inflows in the

Philippines with regards to its infrastructure spending, population, interest rates,

and total customs duties collected. It is also noted that according to Kindleberger

(1969), in a perfectly competitive economy, FDI wouldn’t exist. The rise in FDI is

regarded by traditional theories as being motivated by the differences in the costs

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of domestic versus foreign production or the internalization of transaction costs

involved in exporting or licensing a product to another country. However, it is

also noted that although there are many theories attempting to explain FDI, there

is still no single theory that offers a sufficient explanation for the determinants of

FDI. The difficulty in developing a general theory of FDI stem from two facts:

first is that the determinants of FDI are likely to differ between major sectors in

which foreign investors are engaged, and the second is that the relative

importance of supply factors is likely to differ between host countries with

relatively restrictive attitudes towards FDI and host countries that are more open

to FDI. (Agarwal, Gubitz, & Nunnemkamp, 1991)

Irving Fisher’s (1930) theory of investment stated that the optimum

condition for the firm’s investment decision is that marginal efficiency of

investment is equated with rate of interest and he added a condition that

investment in any time period yields output only in the next period. When the rate

of interest rises, to equate the marginal efficient of investment and interest rate, it

must be that investment declines, thus there is a negative relationship between

investment and interest rate. With regards to the customs duties as a

representation of tariffs of the host country, the institutional theory suggests that a

company’s decision to invest would depend upon the institutional forces that have

an influence on it, especially on regulations and incentives. A number of authors

such as Bond and Samuelson (1986), have concluded that higher tariffs would

discourage FDI as this would decrease the profits on the investor’s side.

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In principle, public infrastructure should have a significance influence on

foreign firms’ costs and revenues and hence on their investment decisions.

Infrastructure availability promotes both horizontal and vertical types of FDI.

Khadaroo and Seetananah (2008) claim that gains rendered by infrastructure

growth are associated with greater accessibility and reduction in transportation

costs. Furthermore, public goods reduce the cost of doing business for foreign

enterprises which leads towards maximization of profit, thereby increasing the

inward inflows of foreign direct investments. On the other hand, poor

infrastructure causes increase in transaction cost and limits access to both local

and global markets which ultimately discourages FDI in developing countries. A

greater efficiency can be achieved in extending infrastructure facilities, if not by

increasing government spending for infrastructures, then by considering

commercial principle and shifting liability for provisioning of infrastructure

liabilities through management contracts and leases. (Mlambo, 2006) Population,

on the other hand, is used as a proxy for market size. According to Chakrabarti

(2001), a large market is necessary for efficient utilization of resources and

exploitation of economies of scale. Therefore, it is expected that an increase in a

host country’s population would also lead to an increase in the FDI inflows.

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Conceptual Framework

FDI

Population

Interest Rate

Customs Duties

Infrastructure Spending

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Problem Statement and Thesis Statement

Foreign investors are profit-oriented individuals who, more often than not,

place their money on countries where they could have great sources of revenue.

These areas are those that provide adequate infrastructure, high numbers of

population, low taxes on foreign products and low interest rates. In order to have a

deeper analysis regarding the country’s foreign investment inflows, this study

aims to answer the following questions:

1. Is there a relationship between foreign direct investments and

infrastructure expenditure?

2. Is there a relationship between foreign direct investments and population?

3. Is there a relationship between foreign direct investments and total

customs duties?

4. Is there a relationship between foreign direct investments and interest rate?

5. Is there a relationship between the four factors (infrastructure expenditure,

population, customs duties, and interest rate) and foreign direct

investments?

Hypothesis

1. Infrastructure Expenditure and FDI

H0: There is no significant relationship between infrastructure expenditure

and FDI.

H1: There is a significant relationship between infrastructure expenditure

and FDI.

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2. Population and FDI

H0: There is no significant relationship between population and FDI.

H1: There is a significant relationship between population and FDI.

3. Total Customs Duties and FDI

H0: There is no significant relationship between total customs duties and

FDI.

H1: There is a significant relationship between total customs duties and

FDI.

4. Interest Rate and FDI

H0: There is no significant relationship between interest rate and FDI.

H1: There is a significant relationship between interest rate and FDI.

5. Infrastructure Expenditure, Population, Customs Duties, Interest Rate and

FDI

H0: There is no significant relationship between all the determinants

(infrastructure expenditure, population, customs duties, and interest rate)

and FDI.

H1: There is a significant relationship between all the determinants

(infrastructure expenditure, population, customs duties, and interest rate)

and FDI.

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Scope and Limitations

The purpose of this study is to determine how infrastructure expenditures,

population, custom duties and interest rate relate to foreign direct investments.

Although there are many factors that can affect FDI, this study will only cover

four independent variables that are measured on how these affect the dependent

variable in the Philippine setting. The scope of the time is patterned on the years

1990-2012, a duration of 23 years using annual data of the variables. This study

takes FDI in general, no specific international corporations or country. It will also

only cover the macroeconomic perspective of FDI, and any political influence or

government control will not be taken into consideration aside from the

aforementioned variables.

Significance of the Study

Despite the government’s attempts in encouraging foreign investors for

the country, the Philippines is still marginally behind in numbers as compared to

their neighboring Asian countries. Given the current situation of the country in the

global competitive market, this study will provide a significant contribution in

determining and evaluating the impact of infrastructure spending, population,

custom duties and interest rate to foreign direct investments. It will analyze how

each factor relates to investment, i.e. whether an increase in the population

automatically presents an increase of investment inflows too. Aside from that, it

will also be able to determine how each factor, in relation to other independent

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variables, relates to FDI. It will also aid in seeing how the constant and annual

adjustment of the controllable variable, the budget for infrastructure spending,

affects the investment flows.

The study will also be beneficial in projecting if and when foreign direct

investment increases or decreases based on the results of the model. It will be able

to identify the role of each given determinant, which may support the government

in their decisions of controlling these factors in order to boost investments in the

country.

Definition of Terms

1. FDI

An investment made by a company or entity based in one country,

into a company or entity based in another country (Investopedia).

Foreign Direct Investment is the Dependent Variable in the study.

This research will test how the determinants will affect the inflow

of FDI in the Philippines. Before investing in a country, investors

consider many factors on investing in a country. This will trace the

pattern of foreign investments from 1990-2012. The importance of

this study is that it will make a model on determining on how the

factors will affect the inflow of foreign investments in the

Philippines having low investments in the past years.

2. Infrastructure Expenditures

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Includes all government consumption and investments for

infrastructure construction and development. (Investopedia)

Infrastructure Expenditures is an Independent Variable in the

study. It is used to determine how the government’s effort in

developing the country’s infrastructures would affect the FDI

inflows. It is also used to represent the quality and priority level for

infrastructure development in the Philippines since there is

insufficient data from other indicators to provide such knowledge

regarding infrastructure quality.

3. Population

The total number of persons inhabiting a country, city, or any

district or area. (Investopedia)

Population is an Independent Variable in the study. It is used to

represent the market size of an economy as it shows the number of

possible consumers that an investor considers. It is assumed that a

higher number of population would yield to an increase in

investment inflows.

4. Total Customs Duties Collected

Customs and other import duties are all levies collected on goods

that are entering the country or services delivered by nonresidents

to residents. They include levies imposed for revenue or protection

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purposes and determined on a specific or ad valorem basis as long

as they are restricted to imported goods or services. (Investopedia)

Total Customs Duties Collected is an Independent Variable in the

study. It is used to represent both imports and tariff rates in the

country. It is assumed that a higher level of duties would lead to a

decrease in FDI inflows as this would discourage profit-oriented

investors in placing their money in the economy.

5. Interest Rate

The amount charged, expressed as a percentage of principal, by a

lender to a borrower for the use of assets. (Investopedia)

Interest Rate is an Independent Variable in the study. It is

considered to be one of the important factors of market stability. A

country with higher interest rates implies an unstable economy,

thereby aiding in assuming that it will reduce FDI.

6. Horizontal FDI

Foreign direct investment by a firm to establish manufacturing

facilities in multiple countries, all producing essentially the same

thing but for their respective domestic or nearby markets.

7. Vertical FDI

Foreign direct investment by a firm to establish manufacturing

facilities in multiple countries, each producing a different input to,

or stage of, the firm’s production process.

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8. Public Good

A commodity or service that is provided without profit to all

members of a society, either by the government or a private

individual or organization. (Investopedia)

Public goods such as infrastructures are an important aspect in this

study. Investors look at the quality and accessibility of public

goods in the host country as this would help them in adjusting

costs due to the availability of said necessities.

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CHAPTER 2: REVIEW OF RELATED LITERATURE

Imad A. Moosa (2002) defines foreign direct investment (FDI) as the

process whereby residents of one country (the investor country) acquire

ownership of assets for the purpose of controlling the production, distribution and

other activities of a firm in another country (the host country). It plays an

extraordinary and growing role in global business which involves an agreement

between both parties with regards to investing foreign assets into domestic

structures, equipment and organizations. The attraction of FDI constitutes a

fundamental element to support strategies that aim to achieve sustained economic

growth especially in developing countries like the Philippines. The outcomes of

foreign direct investments are far more important for developing countries

compared to developed countries as developing countries are mostly short of

capital, lack of access to modern technology, etc. FDI resolves these issues and at

the same time providing benefits to foreign investors. (Rehman, Ilyas, Alam, &

Akram, 2011)

Less developed countries, especially those classified as emerging

countries, have been keen in attracting investment to help with their development

in vital aspects. Initially, they took loans from international commercial banks.

But in the 1980s, the drying-up of commercial bank lending due to the debt crisis,

forced many countries to reform their investment policies so as to attract more

stable forms of foreign capital, and FDI appeared to be one of the easiest way to

get foreign capital without undertaking any risks linked to the debt. Thus, it

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became an attractive alternative to bank loans as a source of capital inflows.

(Erdal Demirhan, 2008) Larrain, et al., (2000) adds that the high demand for FDI

is due to a rise in competition in the global market requiring an increase in

financial resources and technology, which would be difficult to obtain under an

independent policy.

A country with a great market size and high income that has market oriented

policies and steady government is the most likely to interest foreign investments.

Market-seeking investors will be attracted to a country with a large and fast

growing local market. Resource-seeking investors will look for a country with

abundant natural resources. Efficiency-seeking investors will weigh more of

geographical proximity to the home country to minimize transportation costs and

optimize for locations with lower labor costs. (Hoang, 2006)

A. Infrastructure Expenditure and Foreign Direct Investments

In many studies, infrastructure spending is considered as one of the

most common determinants of foreign direct investments as this provides

efficiency in transportation of goods and services that is vital to the

production system of said commodities. More FDI is likely to occur in

countries with good physical infrastructure such as bridges, ports,

highways, etc. Some countries with poor infrastructure may be

unattractive hosts for FDI for a variety of other reasons, and even

substantial investments in infrastructure might not bring FDI pouring in. A

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country with more infrastructures would be expected to attract more FDI

as well as more domestic investment. (Glass) Kumar’s (2001) cross-

country study reports that infrastructure availability does contribute to the

relative attractiveness of a country as a location site for FDI inflows. In

terms of increasing profits for the profit-oriented investor, Haughwout

(2001) supports Glass’ and Kumar’s claim by saying that the availability

of many public goods do in fact lower the cost of private firms.

Empirical studies propose that public goods such as infrastructure have

vital impact on cost structure and productivity of private firms. Poor

infrastructures causes increase in transaction costs and limits access to

both local and global markets which ultimately discourages FDI.

(Mlambo, 2006) Erenberg (1993) said that if such kinds of infrastructure

were to not extend to local and multinational enterprises publicly, then

these enterprises would be operating less efficiently and they would be

forced to build their own infrastructure which results in duplication and

wastage of resources. In contrast to the positive relationships the previous

studies have provided, Shepotulylo (2006) and Bronzini (2004) were not

able to find any correlation between the measure of infrastructure stock

and FDI. Bae (2008) adds that investments in public goods do not pose

statistically substantial direct influence on production performance in

private business firms.

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B. Population and Foreign Direct Investments

Billington (1999) is the first author to consider population as a

variable determinant to FDI. Population implies a more concentrated

consumer and labor market as well as a more integrated infrastructure. In

relation to this, Akin’s (2009) study shows that in developing countries,

population is a crucial indicator for market seeking investors. This

suggests that FDI takes into account the size of the market in terms of

aggregate size. The population of a country may not be important in itself,

but it has important implications for its economic growth. A large

population implies a great number of middle class citizens with spending

power and an appetite for goods and services offered by MNEs. This in

turn, becomes a good and attractive area for investors banking on market

size and purchasing capability. (Aziz & Makkawi, 2012) Economies of

scale is then possible because of a large population provides a large

domestic market without having to depend on exports.

There are also studies which say that population is negatively

related with foreign investment inflows. Thomas Robert Malthus’ theory

about population has been dangerously and generally accepted by most

people in the late 19th and early 20th century. (1992) This implied that

countries with large populations were not expected to experience high

levels of foreign investments, which eventually lead to thinking that they

were not expected to experience growth. With this fear in mind,

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governments of many countries have passed laws that would try to avoid it

as much as possible: like China’s one-child policy and India’s family

planning program.

C. Total Customs Duties and Foreign Direct Investments

Generally, taxes collected become part of the country’s revenue

that the government can use for improvement of public welfare. Taxes

collected from imported or foreign products, also known as tariffs, are part

of the tax revenue which is one of many factors when it comes to foreign

direct investments. Not only do they provide money for budget spending,

but they also serve a purpose of protecting the nation’s local goods by

levelling the competition field against the foreign items. In this study, the

total amount the country receives from customs duties serves a proxy

variable for both imports and tariff rates combined. Hence, literature

behind imports and tariff rates will also be applied in relation to its effects

on the inward inflow of FDI.

Many recent models highlight the effect of customs duties on FDI

within the context of horizontal and vertical specialization within MNEs.

Horizontal FDI is associated with the market seeking behavior of investors

and is motivated by lower trade costs. Hence, high tariff barriers induce

firms to transfer overseas production to countries with lower trade costs.

(Aqeel & Nishat, 2005) A study by Pervez and Malik (2013) concludes

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that lower tariff structures increase the foreign direct investment in a

country. Tariff structures should be framed out in a way to provide

maximum tax incentives to foreign investors in order to promote FDI.

Although a developing country might need higher tax rates in order to

create more tax revenues, for Pervez and Malik, the funds generated

through higher tariffs may be highly insignificant against the overall

economic benefits that could come into the stream due to the increased

FDI over the long run. A careful investigation and analysis is required as

to what extent the tariff structures may be increased without adversely

affecting the FDI.

In this study, since total customs duties is used to represent the

tariff rates in the country, it is therefore safe to assume that it also has a

negative relationship with FDI. Imports, on the other hand, serve as an

indicator of the existing market for the exports of the home country firms.

Higher imports in the host economy encourage the TNCs to produce

locally for market-seeking ventures. (Culem, 1998) However, in contrast

to previous expectation, such ventures become more desirable when there

are high trade barriers (both tariff and non-tariff) on imports. Nevertheless,

due to the existence of import quotas in the Philippines as determined by

Republic Act No. 650, the volatility of the amount collected from duties is

therefore more affected by tariff rates. The researchers then expect that

FDI will react inversely with duties collected annually.

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D. Interest Rates and Foreign Direct Investments

Interest rate mainly measures the economic stability of an

economy. Many financial decisions involve a trade-off between present

and future consumption. A company’s investment choices also involve

such choice. Owners may give priority to present consumption by taking

out dividends, or they can invest in the company and thereby lay the basis

for larger profits later. By placing capital at the disposal of others, one’s

own consumption is postponed. Human beings require compensation for

this, and interest rates provide said compensation. The interest rate is a key

variable in a person’s choice between consumption now or in the future.

(Bergo, 2003)

The use of the interest rate variable as the determinant of FDI has

not been quite common in many studies. But regardless of the absence of

strong theoretical reasons within the OLI framework about how it exactly

affects FDI, the researchers are still interested in using it. Cavallari and

D’Addona’s (2012) study found that with as regards to nominal

uncertainty, interest rate volatility in the host country has a negative effect

on FDI. A rise in domestic volatility, on the other hand, has no significant

impact on foreign investments. These results are compatible with the

predictions of recent models that explain the mode of foreign market

access in an environment with sticky prices. An increase in foreign interest

rate volatility is expected to reduce the profitability of multinational sales

25


relative to exports, leading to a drop in foreign investments. A rise in

domestic volatility, on the contrary, has only a minor effect on the relative

attractiveness of multinational sales. Although the relationship between

FDI and interest rates is not clear, in principle if the host country has

relatively higher rates this will deter firms from investing in expansions of

local capital markets and this may subsequently lead to an increase in FDI.

On the other hand, if the host country has much higher interest rates than

the international market—as this imply an unstable economy, this will

reduce FDI. (Mold, 2003) Although interest rate is expected to be

significantly related to FDI, Shylajan’s (2011) study shows that interest

rates are not important factors in explaining FDI inflows. The similar

result happened in the study made by Shahzad and Zahid. (Shahzad &

Zahid)

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CHAPTER 3: METHODOLOGY

3.1 Overview

This chapter presents the methodology which is used to investigate

and analyse the effect of Infrastructure Spending, Interest Rate, Total

Custom Duties and Population to Foreign Direct Investments in the

Philippines. This will define the level of inflow of foreign direct

investments in the Philippines. It also describes the procedures that were

constructed to acquire the needed and most useful data information to the

study as well as details on how the accumulated data were analysed,

interpreted, and how the conclusion was drawn.

3.2 Research Design

The study uses a formal procedure where the research has

developed and there are already hypothesis to be tested that is the effect of

the determinants to FDI. The researchers have formulated its hypotheses

to answer the research questions. Formal study uses precise procedures for

the research to be answered and it begins with the hypothesis. The

research design is a quantitative study which will use numbers and

statistics on answering the research problems. Quantitative data are

important on the research as it deals with statistics such as Infrastructure

Spending, Interest Rate, Total Custom Duties, Population and Foreign

Direct Investments. Statistical method is very relevant in the study as it is

concerned on the findings of how the four variables (Infra Spending,

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Interest Rate. Custom Duties, Population) affect Foreign Direct

Investments. It is ex post facto as the second hand data will be gathered on

the past studies. The study about the FDI determinants and its effect on

Foreign Direct Investments involve on the measured variable on the past

years of studies about the related variable. Libraries and online sources

will be the sources of the second hand data. Longitudinal will be the time

frame of the study which involves overtime data from 1990-2012. This

time frame is relevant to know the pattern on how the four variables affect

the inflow of foreign direct investments. The purpose of our study is to

know the relationship on our research problems.

3.3 Data Gathering Procedures

3.3.1 Secondary Data

Collection

The statistics and facts used in this study are from

secondary data collection. The statistics used will be from

1990-2012. For this research, a significant amount of publicly

published data pertaining to the five variables at the academic

level is required. Three methods of collecting secondary data

will be applied. This includes using online resources with

appropriate citation and critical analysis for the findings,

library search and indexing through written texts that have

already done similar works in line of the research topic, and

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gathering data from newspapers, magazines, journals and other

similar periodicals. Most of the statistical data were obtained

from government agencies such as BSP, PIDS, ADB, DTI and

DBM. The data that will be collected are the foreign direct

investments, infrastructure spending, interest rate, total custom

duties, and population.

3.4 Treatment of Data

The important assumption of this research is and econometric model

which represents the determinants of FDI using variables: Infrastructure

Spending, Interest Rate, Total Custom Duties, and Population. Linear Regression

will be used to test the relationship of an individual determinant and Foreign

Direct Investments using Microsoft Excel and Multiple Regression to test the

effect of the collaborated independent variables to FDI. This will test if the

individual variables have significant effect to FDI. The data in millions and

billions are divided to have smaller values.

Dependent Variable

A. Foreign Direct Investments

Foreign Direct Investment is the Dependent Variable in the study. The

data are obtained from Asian Development Bank. This research will test

how the determinants will affect the inflow of FDI in the Philippines.

29


Before investing in a country, investors consider many factors on

investing in a country. This will trace the pattern of foreign investments

from 1990-2012. The importance of this study is that it will make a model

on determining on how the factors will affect the inflow of foreign

investments in the Philippines having low investments in the past years.

Independent Variables

1. Infrastructure Spending

The data are obtained from ADB. Infrastructure spending indicates that a

country with many stable building structures and ports is a good area for

investments. Since better infrastructure means low cost of transporting

goods or other necessary factors considered by investors and convenience,

this will test how this infrastructure spending in the Philippines will affect

the decision of investors.

2. Interest Rate

The data of Interest Rate are obtained from BSP. Interest Rate is a

common factor on that makes the decision of foreign investors on spending on

a specific country. It is believed that higher interest rate would actually

decrease the inflow of FDI because it will be more expensive on investing

30


in a country. This study will determine how interest rate in the Philippines affects

the inflow of its FDI.

3. Total Custom Duties

The data are obtained from DBM. Total Custom Duties are used as a

representation of the tariff rate, this tariffs collected by the government would test

on whether the tariff rate affects FDI directly or inversely. It is believed that lower

rates of taxes would actually increase the inflow of FDI but this study will test on

how do the total custom duties or tax rate would affect the FDI inflow in the

Philippines.

4. Population

The data of population are obtained from PIDS. Investors compare

population as an indication of market size and consider the countries with bigger

numbers of residents. This study will test on whether the size of the Philippine

population would affect its inflow of FDI.

Regression Analysis

Linear Regression

Simple Regression will be used on determining the effects of the Four

Variables to Foreign Direct Investment. This will define the relationship of the

variables to FDI on whether it will increase of decrease the inflow of FDI.

31


Infrastructure Spending and FDI

Infrastructure is one of the important factors considering on investing in a

country. Better infrastructure of a country would cost the investors less investing

in a country. Linear Regression will test whether the infrastructure spending in the

Philippines especially on transportation will increase or decrease the inflow of

FDI.

Y=a+b1X1

Where: Y=Foreign Direct Investments

X1= Infrastructure Spending

Interest Rate and Foreign Direct Investments

Higher interest rates would cost more cost on investing in a country. This factor is

essential considering investing in a country. It will test on whether the Interest

rate affects the FDI positively or negatively.

Y=a+b2X2

Where: Y= Foreign Direct Investments

X2= Interest Rate

Total Custom Duties and Foreign Direct Investments

Investors, being profit-oriented individuals, are more inclined to invest in

countries with lower rates of taxes need to be collected as high taxes would mean

a decrease in their total profits. Total Custom Duties will be the representation of

tax rates or the taxes collected from by the government. This study will define the

relationship on how the tax rate will affect the inflow of FDI.

32


Y=a+b3X3


X3= Total Custom Duties

Population and Foreign Direct Investments

Investors compare population as an indication of market size and consider the

countries with bigger numbers of residents. This study will define the relationship

of the size of the Philippine population and the inflow of FDI.

Y=a+b3X4


X4= Population

Multiple Regressions

Multiple Regressions will be used in this study to determine on how the

four determinants of FDI affect the inflow of Foreign Direct Investment in the

Philippines. This will serve as a framework on determining the inflow of FDI

using these four variables. This can trace the pattern on how the foreign investors

decide on investing in a country.

Y=a+b1X1+b2X2+b3X3+b4X4

Where Y= FDI

X1= Infrastructure Spending

X2= Interest Rate

X3= Total Custom Duties

X4= Population

33


CHAPTER 4: DATA PRESENTATION AND ANALYSIS

The study will test the relationship of each independent variable to the

dependent variable using Linear Regression and Multiple Regression. In the study

of the relationships of the determinants of Foreign Direct Investments, this will

test if the determinants have relationship to the FDI in the Philippine setting.

In a study of Foreign Direct Investment (Y) for the Philippine setting,

three independent variables were considered: X1: Infrastructure Spending, X2:

Interest Rate, X3: Total Custom Duties, X4: Population

Data Results and Analysis

Question 1: Is there a relationship between the Infrastructure Spending in the

Philippines and Foreign Direct Investments?

The study uses Linear Regression as its statistical tool to test the

relationship between two variables; Foreign Direct Investment (Y) and

Infrastructure Spending (X1).

Linear Regression Results

Multiple Regression 0.441772

R Square 0.195163

T Stat P-Value

Intercept 3.81 0.001014

34


Infra Spending 2.25 0.034817

Regression Equation Y=994.33+6.16X1

The Independent Variable (X1) is statistically significant (because the

results are above the t table value 2.07 with 22 degrees of freedom at 5% level of

significance) so we will accept the alternative hypothesis and it proves that there

is a significant relationship between the two.

The r-square shows that the model can explain the variation 19% in FDI. Also the

data shows that there is a direct relationship between the two because of the

positive coefficient of Minimum Wage.

Question 2: Is there a relationship between the Philippines’ Interest Rate and

Foreign Direct Investments?


relationship between the two variables; FDI(Y) and Interest Rate (X2).



R Square 0.181477

T Stat P-Value

35


Intercept 6.58 1.6E-06

Interest Rate -2.15 0.046278

Regression Equation Y=2043.05-112.239X2




is a significant relationship between the two.

The r-square shows that the model can explain the variation 18% in FDI. Also the

data shows that there is an inverse relationship between the two because of the

positive coefficient of GDP.

Question 3: Is there a relationship between the Philippine Total Custom Duties

and Foreign Direct Investments?


relationship between the two variables FDI (Y) and Foreign Total Custom Duties

(X3).



R Square 0.23473

36


T Stat P-Value

Intercept 2.36 0.02776

Total Customs -2.53 0.019138

Regression Equation Y=754.2742+5.2338X3




is a significant relationship between the two variables. The r-square shows that

the model can explain the variation 23% in FDI. Also the data shows that there is

an inverse relationship between the two because of the positive coefficient of the

Total Custom Duties.

Question 4: Is there a relationship between the Philippine Population and

Foreign Direct Investments?


relationship between the two variables FDI (Y) and Foreign Total Custom Duties

(X4).



R Square 0.232204

37


T Stat P-Value

Intercept -1.18807 0.248069

Population 2.520125 0.019893

Regression Equation Y=-1330.97+35.53482X4




is a significant relationship between the two variables. The r-square shows that

the model can explain the variation 23% in FDI. Also the data shows that there is

a direct relationship between the two because of the positive coefficient of

Population.

` Question 5: Is there a relationship with the Philippines’ Infrastructure Spending,

Interest Rate, Total Customs Duties and Population to FDI inflows in the Philippines?

Multiple Regression Results

The study uses Multiple Regression to test the relationship between all the

determinants and the Foreign Direct Investment. The Independent variables are

transformed by raising the variables to 12 using the Multicollinearity test. The

variables are transformed because some of the independent variables are

insignificant.

38


Multicollinearity Test

In case the variables are not significant or they have a very low or a very

high P-value, the data will be transformed. This Multicollinearity test will

transform the variables to be significant so the model will be accepted. But there

are instances that some of the variables are insignificant depending on the model

involved.


R Square 0.418273

T Stat P-Value

Intercept 5.72 1.97E-05

Infra Spending 0.66 0.515221

Interest Rate -1.58 0.130426

Total Custom -2.31 0.03267

Population 2.66 0.015935

Regression Equation Y=1216.707+1.05E-26X1-4.8E-10X2-1.9E-

26X3+4.66E-21X4

The R-squared value means that 41.8% of the variation in FDI can be

explained by the regression on independent variables. There is a 1216.707 mean

response of FDI when all of the explanatory variables have a value of zero.

39


The t table value of the analysis is 2.07 with 22 degrees of freedom at 5%

level of significance. The results of the variables are as follows:

Infrastructure Spending (X1) is not statistically significant having a

t statistics of 0.66 but has a positive relationship with FDI base on

the model. Also the P-value(Infrastructure Spending) .515> 0.05 Critical

Value

Interest Rate (X2) is not statistically significant having a t statistics

of -1.58 and has a negative relationship with the FDI base on the

model. Also The P-value(Interest Rate) 0.13> 0.05 Critical Value

Total Custom Duties (X3) is significant having a t statistics of -2.31

and has a negative relationship with FDI. Also the P value (Total Customs

Duties) 0.03< 0.05 Critical Value

Population (X4) is statistically significant having a t statistics of

2.66 and has a positive relationship with the FDI base on the

model. Also The P-value(Population) 0.015< 0.05 Critical Value

In this study, the Infrastructure Spending and Interest Rate are retained to

satisfy the determinants of FDI. It is because the primary consideration in

deciding an independent variable belongs in an equation is whether the variable is

essential to the regression on the basis of theory. If it is an ambiguous yes, then

the variable definitely should be included in the equation, even if it is lacking in

statistical significance. (Wuncsch, 2004)

40


F-Test for the Overall Fit of the Model

To test the statistical significance of the regression relation between FDI

(Y) and its Determinants Minimum Wage (X1), GDP (X2), Foreign Exchange

(X3), the study will use the F-Test. The hypotheses of the regression relation will

be:

H0: X1 = X2 = X3 = 0

H1: not all Xi (i=1, 2, 3) equal zero

Base on Figure 8 the F statistics is 3.24. The F critical value is 2.93 with

5% level of significance. Since F statistics 3.24 > 2.93 F critical Value, the null

hypothesis will be rejected. This means that the model can significantly determine

the FDI in terms of Infrastructure Spending, Interest Rate, Total Custom Duties

and Population. Therefore, the model Y=1216.707+1.05E-26X1-4.8E-10X2-1.9E-

26X3+4.66E-21X4 is statistically significant.

Heteroscedasticity Test

H0: The model is Homoscedastic

H1: The model is Heteroscedastic

ESS1 6.82121E-13

ESS2 56857.65007

ESS2/ESS1 8.33

41


The data 8.33 is below the F critical value which is 8.85 with 5% level of

significance. Therefore, the null hypothesis will be accepted so this means that the

model is Homoscedastic.

Autocorrelation Test

Autocorrelation is used when the data are in time series to know whether

there is a correlation among the variables or it does not exist. To test the

correlation of the variables Durbin-Watson is used.

Durbin-Watson 1.58

dL 0.9861

dU 1.785

The Autocorrelation test will test the model if it is auto correlated or not.

Having 23 as the number of observation and 4 as the number of explanatory

variables, the value of dU and dL will test the autocorrelation of the model. Since

the Durbin-Watson value 0.9861(dL) < 1.61 < 1.785 (dU), this proves that the

model is inconclusive will accept the autocorrelation.

42


CHAPTER 5: SUMMARY, CONCLUSIONS, RECOMMENDATION

Given the increasing competition with regards to encouraging foreign

direct investments, the Philippines continues to struggle with this goal despite the

abundance of natural resources and competitive labor force. However, the

existence of the aforementioned general qualities is theorized to be insufficient in

attracting FDI; thus, four different variables were presented to have an effect with

FDI: infrastructure expenditures, interest rates, population and the total amount of

custom duties collected. The study used a timeline-based duration of 23 years,

from 1990-2012. The researchers find this thesis to be significant in determining

whether these given factors do affect FDI, specifically with the issues regarding

the government’s control over the infrastructure budgets and tariff rates in the

country. The uncontrollable variables—population and interest rates—are also

being focused on as both demonstrate irregular patterns throughout the years. In

order to find the relationship of each factor to FDI, linear regression was used.

Infrastructure spending is found to be insignificant and directly related to

FDI. Kumar’s (2001) explains the positive relationship between the two variables

by reporting thru his study that infrastructure availability aids in contributing to

the relative attractiveness of a country, thereby increasing FDI inflows. Not only

that, in helps in lowering the costs of the private firms in budgeting for materials

needed. The insignificance of infrastructure expenditures is explained by many

different studies such as Shepotulyo’s (2006), Bronzini’s (2004), and Bae’s

(2008). Their studies show no correlation between infrastructure and FDI, and add

43


that investments in public goods do not automatically pose substantial direct

influence on production performance of private firms.

Interest rate is found to be also insignificant but is inversely related to

FDI. The result is in line with the theoretical framework aforementioned and with

supporting studies available. Cavallari and D’Addona’s study (2012) justifies the

negative relationship by saying that with regards to nominal uncertainty, interest

rate volatility in the host country does have a negative impact on FDI. An increase

in foreign interest rate volatility is expected to reduce the profitability of

multinational sales relative to exports, leading to a drop in foreign investments.

The insignificance of the variable is thereby explained by Shylajan in relation to

his study with regards to interest rates implication. According to him, there is an

absence of strong theoretical reasons as to how interest rates could affect FDI,

therefore these [interest] rates are not important factors in explaining FDI inflows.

(Shylajan, 2011)

Total custom duties collected is found to be a significant variable and is

negatively related to FDI. The researchers found the result to be in line with the

expected outcome backed up by supporting theories and studies. Used as a proxy

variable for tariff rates (and due to present policies about import quotas), the

negative relationship is thereby logical and understandable. A study by Pervez

and Malik (2013) concludes that lower tariff structures increase the foreign direct

investment in a country. Tariff structures should be framed out in a way to

provide maximum tax incentives to foreign investors in order to promote FDI.

44


According to them, if the government would still push for higher tariff rates, a

careful investigation and analysis is required as to what extent the tariff structures

may be increased without adversely affecting the FDI. In this case, since there are

import quota policies in the Philippines, a high amount of custom duties collected

means a high rate of tariff. Therefore, the higher the amount of duties collected,

the less FDI would flow in the country.

Lastly, population is found to be significant and has a direct relationship

with FDI. Akin’s (2009) study shows that in developing countries, population is a

crucial indicator for market seeking investors. This suggests that FDI takes into

account the size of the market in terms of aggregate size. A high number of

population implies a great number of middle class citizens with spending power,

thereby being more attractive to investors who are profit oriented and market

seekers.

The researchers recommend a deeper analysis of the study using more

additional factors as determinants of foreign direct investments in the Philippines.

The addition of other variables that can measure the market size should also be

considered not only the population. It also recommends further studies that

consider non-quantifiable data such as the role of government to fully observe the

inflow of FDI. Also, it recommends that the data used will be quarterly to further

observe the effect of different factors of FDI to the investment decisions of

foreign investors. Using quarterly data and extending the scope of year will also

increase the r-square of each independent variable. Studying the FDI inflows from

45


a microeconomic perspective is also recommended with regards to the behavior of

foreign investors and multinational companies inside the country. The use of other

statistical tools and quantifying methods is also suggested to provide a more

profound examination of the study.

46


APPENDIX AFigure 1: Linear Regression of FDI and Infrastructure Spending

SUMMARY OUTPUT

Regression StatisticsMultiple R 0.441772129R Square 0.195162614Adjusted R Square 0.156837024Standard Error 747.4305431Observations 23

ANOVAdf SS MS F Significance F

Regression 1 2844785.076 2844785.076 5.092227279 0.034816738Residual 21 11731700.75 558652.4167Total 22 14576485.83

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%Intercept 994.3301493 260.7565505 3.813250894 0.001014459 452.0572168 1536.603082 452.0572168 1536.603082Infrastructure Spending 6.160803183 2.730130742 2.256596392 0.034816738 0.483185494 11.83842087 0.483185494 11.83842087

47


Figure 2: Linear Regression of FDI and Interest Rate

SUMMARY OUTPUT




Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%Intercept 2043.051614 310.1598687 6.58709208 1.59722E-06 1398.038858 2688.064371 1398.038858 2688.064371Interest Rate -112.2394602 52.01636149 -2.157772228 0.042678285 -220.4134057 -4.0655147 -220.4134057 -4.0655147

48


Figure 3: Linear Regression of FDI and Total Customs Duties

SUMMARY OUTPUT




Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%Intercept 754.2742042 318.9919115 2.364555893 0.027760449 90.8942086 1417.6542 90.8942086 1417.6542Total Duties / 1BPHP 5.233800172 2.062197806 -2.53797194 0.019137542 0.945225064 9.522375279 0.945225064 9.522375279

49


Figure 4: Linear Regression of FDI and Population

SUMMARY OUTPUT




Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%Intercept -1330.970772 1120.278503 -1.18807133 0.248068958 -3660.717457 998.7759138 -3660.717457 998.7759138Population 35.53482481 14.10042221 2.520124879 0.01989298 6.211391575 64.85825805 6.211391575 64.85825805

50


Figure 5: Mulitple Regressions (Original Data)

SUMMARY OUTPUT




Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%Intercept 1302.282136 2856.696878 0.455869906 0.653935365 -4699.415298 7303.97957 -4699.415298 7303.97957Infrastructure Spending 0.159792307 6.949871697 0.022992123 0.981909525 -14.44134632 14.76093093 -14.44134632 14.76093093Interest Rate -74.92179398 59.13944572 -1.266866692 0.221350513 -199.1691589 49.32557099 -199.1691589 49.32557099Total Customs Duties 3.974113347 6.922936222 0.574050261 0.573038035 -10.57043595 18.51866264 -10.57043595 18.51866264Population -0.048132456 43.76710552 -0.00109974 0.999134631 -91.99940908 91.90314417 -91.99940908 91.90314417

51


Figure 6: Multicollinearity Test

SUMMARY OUTPUT




Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%Intercept 1216.706671 212.392581 5.728574254 1.97416E-05 770.4864168 1662.926926 770.4864168 1662.926926Infrastructure Spending 1.04956E-26 1.5811E-26 0.663817427 0.515220522 -2.2722E-26 4.37133E-26 -2.2722E-26 4.37133E-26Interest Rate -4.8458E-10 3.0577E-10 -1.58478467 0.130426484 -1.12698E-09 1.57819E-10 -1.12698E-09 1.57819E-10Total Customs Duties -1.86002E-26 8.03718E-27 -2.314274217 0.032669556 -3.54857E-26 -1.71475E-27 -3.54857E-26 -1.71475E-27Population 4.65656E-21 1.75034E-21 2.660375913 0.015935409 9.79234E-22 8.33389E-21 9.79234E-22 8.33389E-21

52


Figure 7: Heteroskedasticity ESS1

SUMMARY OUTPUT

Regression StatisticsMultiple R 0.994453R Square 0.988937Adjusted R Square0.977874Standard Error63.00423Observations 9


Regression 4 1419363 354840.8555 89.39107 0.000364Residual 4 15878.13 3969.533422Total 8 1435242

CoefficientsStandard Error t Stat P-value Lower 95%Upper 95%Lower 95.0%Upper 95.0%Intercept 1.753078 52.82185 0.033188503 0.975114 -144.904 148.41 -144.904 148.41Infrastructure Spending4.63E-19 3.53E-19 1.310202389 0.260299 -5.2E-19 1.44E-18 -5.2E-19 1.44E-18Interest Rate7.65E-11 3.3E-11 2.316404629 0.081457 -1.5E-11 1.68E-10 -1.5E-11 1.68E-10Total Customs Duties2.67E-22 4.17E-23 6.407136255 0.003048 1.52E-22 3.83E-22 1.52E-22 3.83E-22Population 5.22E-20 4.25E-21 12.28438389 0.000252 4.04E-20 6.4E-20 4.04E-20 6.4E-20

RESIDUAL OUTPUT

ObservationPredicted Foreign Direct Investment Residuals E21 197.6672 -2.66717 -2.667174632 235.2498 -7.24976 -7.249759213 492.4323 -1.43231 -1.432307854 441.0017 88.9983 88.998295335 583.8455 -39.8455 -39.84550746 761.6777 -73.6777 -73.6776767 1193.177 28.82294 28.822938318 1231.008 6.991642 6.9916421679 1246.94 0.059549 0.059549303

sum 6.82121E-13

53


Figure 8: Heteroskedasticity ESS2

SUMMARY OUTPUT

Regression StatisticsMultiple R 0.989073R Square 0.978265Adjusted R Square0.95653Standard Error119.2242Observations 9


Regression 4 2559085 639771.1 45.00862 0.001397Residual 4 56857.65 14214.41Total 8 2615942

CoefficientsStandard Error t Stat P-value Lower 95%Upper 95%Lower 95.0%Upper 95.0%Intercept 1421.649 104.5491 13.59792 0.000169 1131.375 1711.924 1131.375 1711.924X Variable 1-7.1E-28 2.86E-27 -0.24741 0.816769 -8.7E-27 7.24E-27 -8.7E-27 7.24E-27X Variable 22.55E-07 1.83E-07 1.394094 0.235741 -2.5E-07 7.63E-07 -2.5E-07 7.63E-07X Variable 3 4.1E-27 2.47E-27 1.658494 0.172557 -2.8E-27 1.1E-26 -2.8E-27 1.1E-26X Variable 41.52E-21 6.7E-22 2.269675 0.085758 -3.4E-22 3.38E-21 -3.4E-22 3.38E-21

RESIDUAL OUTPUT

ObservationPredicted Y Residuals e21 1586.688 4.31156 18.589552 1621.344 13.65618 186.49123 1744.346 -80.3461 6455.4984 1980.375 49.62459 2462.65 2273.249 -33.2487 1105.4746 2312.678 -25.6775 659.33537 2524.098 182.9021 33453.198 2823.875 -111.875 12516.059 3244.347 0.652997 0.426405

sum 56857.65

54


Figure 9: Autocorrelation Test

RESIDUAL OUTPUT

ObservationPredicted Foreign Direct Investment Residuals et-1 e-et-1 (e-et-1)2 e21 815.7421 -285.742 81648.562 1236.98 -692.98 -285.742 -407.2378882 165842.7 480221.33 156.2157 71.78431 -692.98 764.7643247 584864.5 5152.9874 1242.668 -4.66765 71.78431 -76.45195627 5844.902 21.786925 1267.454 323.5461 -4.66765 328.2137039 107724.2 104682.16 1261.598 216.4023 323.5461 -107.1437217 11479.78 46829.977 1276.793 240.2072 216.4023 23.80486061 566.6714 57699.58 1050.69 171.3098 240.2072 -68.89736259 4746.847 29347.069 1325.629 961.3714 171.3098 790.0615518 624197.3 924234.9

10 1357.722 -110.722 961.3714 -1072.093643 1149385 12259.4211 1398.459 841.5412 -110.722 952.2635039 906805.8 708191.712 1446.464 -1251.46 841.5412 -2093.005334 4380671 156616213 1512.369 29.63128 -1251.46 1281.095364 1641205 878.012614 1589.879 -1098.88 29.63128 -1128.510401 1273536 120753515 1688.69 -1000.69 -1098.88 98.18938236 9641.155 100138016 1808.021 -144.021 -1000.69 856.6690821 733881.9 20741.9517 2020.738 686.2624 -144.021 830.2830578 689370 470956.118 2189.325 1055.675 686.2624 369.4121167 136465.3 111444919 819.6691 616.3309 1055.675 -439.3436643 193022.9 379863.720 2741.92 -29.9203 616.3309 -646.2511521 417640.6 895.224421 1723.058 -88.0583 -29.9203 -58.13800694 3380.028 7754.26622 1761.557 -508.557 -88.0583 -420.4983618 176818.9 258629.923 2028.36 1.639525 -508.557 510.1961949 260300.2 2.688041

SUM 13477391 8479537n=23 k=4

DL 1.785 Du 0.9861Durbin-Watson 1.589402 inconclusive

55


APPENDIX BTable 1. Data of Dependent Variable: Foreign Direct Investment

Year Foreign Direct Investment 1990 530.001991 544.001992 228.001993 1238.001994 1591.001995 1478.001996 1517.001997 1222.001998 2287.001999 1247.002000 2240.002001 195.002002 1542.002003 491.002004 688.002005 1664.002006 2707.002007 3245.002008 1436.002009 2712.002010 1635.002011 1253.002012 2030.00

Source: Asian Development Bank

56


Table 2. Data of Independent Variable: Infrastructure Spending

Year Infrastructure Spending1990 18.11991 19.21992 25.61993 20.41994 34.81995 42.61996 42.81997 49.91998 41.71999 55.22000 65.12001 65.72002 59.92003 60.72004 58.62005 51.72006 84.82007 111.52008 143.32009 168.52010 131.22011 159.12012 250.8

Source: DBM

57


Table 3. Data of Independent Variable: Interest Rate

Year Interest Rate1990 9.871991 5.621992 10.701993 7.351994 4.611995 6.631996 6.671997 9.461998 -4.581999 4.872000 4.922001 6.492002 4.782003 6.082004 4.322005 4.122006 4.602007 5.432008 1.122009 5.642010 3.312011 2.542012 3.7

Source: BSP

58


Table 4. Data of Independent Variable: Total Customs Duties

Year Total Customs Duties1990 43

1991 60

1992 68

1993 77

1994 77

1995 98

1996 105

1997 95

1998 76

1999 86

2000 95

2001 96

2002 96

2003 106

2004 122

2005 142

2006 198

2007 209

2008 260

2009 220

2010 259

2011 265

2012 274

Source: DTI

59


Table 5. Data of Independent Variable: Population

Year Population1990 60.70

1991 63.69

1992 65.34

1993 66.98

1994 68.62

1995 68.35

1996 69.95

1997 71.54

1998 73.13

1999 74.72

2000 76.32

2001 77.90

2002 79.48

2003 81.05

2004 82.64

2005 84.21

2006 86.97

2007 88.71

2008 90.46

2009 92.23

2010 94.01

2011 95.80

2012 97.59

Source: PIDS

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Table 6. Multiple Regression Data (Original)

Year Foreign Direct Investment Infrastructure Spending Interest Rate Total Customs Duties Population1990 530.00 18.1 9.87 43 60.701991 544.00 19.2 5.62 60 63.691992 228.00 25.6 10.70 68 65.341993 1238.00 20.4 7.35 77 66.981994 1591.00 34.8 4.61 77 68.621995 1478.00 42.6 6.63 98 68.351996 1517.00 42.8 6.67 105 69.951997 1222.00 49.9 9.46 95 71.541998 2287.00 41.7 -4.58 76 73.131999 1247.00 55.2 4.87 86 74.722000 2240.00 65.1 4.92 95 76.322001 195.00 65.7 6.49 96 77.902002 1542.00 59.9 4.78 96 79.482003 491.00 60.7 6.08 106 81.052004 688.00 58.6 4.32 122 82.642005 1664.00 51.7 4.12 142 84.212006 2707.00 84.8 4.60 198 86.972007 3245.00 111.5 5.43 209 88.712008 1436.00 143.3 1.12 260 90.462009 2712.00 168.5 5.64 220 92.232010 1635.00 131.2 3.31 259 94.012011 1253.00 159.1 2.54 265 95.802012 2030.00 250.8 3.7 274 97.59

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Table 7. Multiple Regression Data (Transformed)

Year Foreign Direct Investment Infrastructure Spending Interest Rate Total Customs Duties Population1990 530.00 1.23635E+15 8.51504E+11 4.09179E+19 2.50345E+211991 544.00 2.50966E+15 988914163.2 2.24523E+21 4.45663E+211992 228.00 7.92282E+16 2.24665E+12 9.50401E+21 6.05437E+211993 1238.00 5.19472E+15 24797322077 4.21907E+22 8.15581E+211994 1591.00 3.15465E+18 91030388.88 4.03817E+22 1.09076E+221995 1478.00 3.57203E+19 7221954124 7.47225E+23 1.03949E+221996 1517.00 3.77855E+19 7724239616 1.70878E+24 1.37142E+221997 1222.00 2.38345E+20 5.15236E+11 5.26866E+23 1.79674E+221998 2287.00 2.7646E+19 85047908.46 3.71626E+22 2.34001E+221999 1247.00 8.0033E+20 178178133.4 1.75393E+23 3.03024E+222000 2240.00 5.79391E+21 199572585.3 5.4077E+23 3.90543E+222001 195.00 6.46821E+21 5602933063 6.30716E+23 4.99261E+222002 1542.00 2.13364E+21 141359240.7 6.32134E+23 6.35109E+222003 491.00 2.50187E+21 2530821459 2.03279E+24 8.04105E+222004 688.00 1.63973E+21 42672480.3 1.13856E+25 1.01409E+232005 1664.00 3.64659E+20 23709272.24 6.56964E+25 1.2725E+232006 2707.00 1.38277E+23 90205243.11 3.66622E+27 1.8732E+232007 3245.00 3.69231E+24 661695829.2 7.12345E+27 2.37385E+232008 1436.00 7.49815E+25 3.79906701 9.6527E+28 3.00136E+232009 2712.00 5.2384E+26 1028512119 1.30719E+28 3.78682E+232010 1635.00 2.60139E+25 1732672.52 9.21392E+28 4.76723E+232011 1253.00 2.63052E+26 72111.51162 1.20524E+29 5.97837E+232012 2030.00 6.19342E+28 6582952.006 1.78218E+29 7.46586E+23

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Table 8. Heteroskedasticity Data (Arranged)

Year Foreign Direct Investment Infrastructure Spending Interest Rate Total Customs Duties Population1990 195.00 1.23635E+15 8.51504E+11 4.09179E+19 2.50345E+211991 228.00 2.50966E+15 988914163.2 2.24523E+21 4.45663E+211992 491.00 7.92282E+16 2.24665E+12 9.50401E+21 6.05437E+211993 530.00 5.19472E+15 24797322077 4.21907E+22 8.15581E+211994 544.00 3.15465E+18 91030388.88 4.03817E+22 1.09076E+221995 688.00 3.57203E+19 7221954124 7.47225E+23 1.03949E+221996 1222.00 3.77855E+19 7724239616 1.70878E+24 1.37142E+221997 1238.00 2.38345E+20 5.15236E+11 5.26866E+23 1.79674E+221998 1247.00 2.7646E+19 85047908.46 3.71626E+22 2.34001E+221999 1253.00 8.0033E+20 178178133.4 1.75393E+23 3.03024E+222000 1436.00 5.79391E+21 199572585.3 5.4077E+23 3.90543E+222001 1478.00 6.46821E+21 5602933063 6.30716E+23 4.99261E+222002 1517.00 2.13364E+21 141359240.7 6.32134E+23 6.35109E+222003 1542.00 2.50187E+21 2530821459 2.03279E+24 8.04105E+222004 1591.00 1.63973E+21 42672480.3 1.13856E+25 1.01409E+232005 1635.00 3.64659E+20 23709272.24 6.56964E+25 1.2725E+232006 1664.00 1.38277E+23 90205243.11 3.66622E+27 1.8732E+232007 2030.00 3.69231E+24 661695829.2 7.12345E+27 2.37385E+232008 2240.00 7.49815E+25 3.79906701 9.6527E+28 3.00136E+232009 2287.00 5.2384E+26 1028512119 1.30719E+28 3.78682E+232010 2707.00 2.60139E+25 1732672.52 9.21392E+28 4.76723E+232011 2712.00 2.63052E+26 72111.51162 1.20524E+29 5.97837E+232012 3245.00 6.19342E+28 6582952.006 1.78218E+29 7.46586E+23

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