Foreign direct investments in Subic Bay Free Port Zone.
Calderon-Kabigting, Leila Y.
The research examined why foreign companies invest in Subic Bay
Freeport Zone. We tested the relationship of these variables: market
size, degree of openness, infrastructure, labor quality, inflation,
taxes, foreign exchange, exports, in promoting foreign direct
investments in Subic Bay. The study examined the presence of
agglomeration in the freeport zone. The paper also identified competitor
host countries, and other investment promotion agencies in the
Philippines. The findings showed that market size, degree of openness,
labor quality, exports, taxes have positive relationships with FDIs
while inflation, infrastructure, foreign exchange rate have negative
relationships with FDIs. We recommend that SBMA continue to take
initiatives in its investment policies, adopting best practices that can
compete with other IPAs and other countries.
INTRODUCTION
The United Nations Conference on Trade and Development (UNCTAD)
referred to the Balance of Payments Manual (BPM-5th edition) in defining
Foreign Direct Investments (FDI) as "an investment made to acquire
lasting interest in enterprises operating outside of the economy of the
investor." Foreign direct investors must have at least 10 percent
of equity ownership and manage the enterprise operating in another
economy.
In the Philippines, the National Statistical Coordination Board
(NSCB) similarly based the definition of FDI on the UNCTAD Balance of
Payment (BOP) manual. FDIs are "investments made by an entity
resident in one economy in an enterprise resident in another
economy." The Philippines, mostly, is a recipient of inward FDI.
Approved foreign direct investments are those foreign investment
commitments that may be generated at present or in the future. These
FDIs are approved and registered with any of the Investment Promotion
Agencies (IPAs)--the Board of Investments (BOI), the Philippine Economic
Zone Authority (PEZA), the Subic Bay Metropolitan Authority (SBMA) and
Clark Development Corporation (CDC). (www.nscb.gov.ph)
Several factors play an important role for companies to decide
whether to invest directly in a foreign host country. These factors
include market size, degree of openness, infrastructure, investments,
labor quality, incentives, and location have empirical positive
relationships with FDI. (Li, Hou, and Chan, 2008; Vogiatzoglou 2008;
Ramirez, 2006; Chakrabarti, 2001). On the other hand, taxes, inflation,
and foreign exchange have negative relationship with FDI (Chakrabarti,
2001; Woodward, Rolfe, 1993). However, there is no study that has
identified factors affecting FDIs for Philippine investment promotional
agencies (IPAs) particularly that of SBMA for Subic Bay Freeport Zone
(Subic Bay).
The paper identifies which of these variables: approved projects,
market size, degree of openness, infrastructure, labor costs, labor
quality, available workforce, taxes, foreign exchange, and exports have
a positive or negative impact on FDI in Subic Bay. The study also
compares FDIs in SBMA with FDIs of other IPAs and competitor countries,
namely, China, India and Vietnam.
The paper is organized as follows. Firstly, we present a review of
literature that focuses on determinants of FDIs and agglomeration
theory. Secondly, we present a regression model and discuss its results
to validate a priori expectations. Lastly, the paper offers policy
recommendations to enhance the growth of FDI in Subic Bay Freeport Zone.
LITERATURE REVIEW
Location choice and FDI
A vast number of research have examined location determinants of
FDI starting with Dunning's (1979) seminal work as cited by Sethi,
Guisinger, Phelan, Berg(2003). The location theory explains why
multinational enterprises (MNEs) evaluate possible locations for more
efficient operations on a regional rather than country-specific bases.
MNEs' location determinants may include market size, market growth,
labor cost, transportation, infrastructure, government policy, and
taxes. (Sethi, Guisinger, Phelan, Berg, 2003; Woodward; Rolfe, 1993).
Market size, represented by Gross Domestic Product (GDP), is the
most significant accepted determinant of FDI, and has a positive
relationship. (Li, Hou, and Chan, 2008; Vogiatzoglou 2008; Ramirez,
2006; Chakrabarti, (2001). Ramirez (2006) also suggests the use of
lagged value of GDP since foreigners make decision based on the past.
Li, Hou, and Chan (2008) measures infrastructure readiness of the
location in three different variables: highways, railways, and
telecommunications. MNEs would invest in locations that have accessible
transportation and telecommunications facilities for more efficient
operations.
The degree of openness is proxied by the ratio between exports and
GDP. Majority of the literature demonstrate that the degree of openness
and FDI has a positive relationship. (Li, Hou, and Chan, 2008;
Vogiatzoglou 2008; Ramirez, 2006; Chakrabarti, 2001). However,
Chakrabarti (2001) presented literature that the relationship of degree
of openness and FDI was observed to be insignificant.
Wage rates are used to determine labor costs. Labor costs may have
different a priori expectations. These can be positive (Li, Hou, and
Chan, 2008; Woodward, Rolfe 2003; Chakrabarti, 2001), negative
(Chakrabarti, 2001) and insignificant or none (Li, Hou, and Chan, 2008;
Chakrabarti, 2001).
Li, Hou, and Chan, (2008) referred to wage rate, as marginal
productivity of labor in the classical economic theory. A higher wage
rate results into higher labor productivity thus having a positive
relationship with FDI. However, higher wages may also be detrimental to
attracting MNEs, since a consideration for inward FDI is cheap labor,
and may have negative or no significant effect on FDI (Chakrabarti,
2001;Woodward, Rolfe, 1993).
Chakrabarti (2001) surveyed literature on taxes and foreign
exchange as determinants that may conclude in three different
observations: positive, negative or insignificant relationship with FDI.
Other possible factors that can have a positive relationship with
FDI are length of income tax holiday, political stability, and
manufacturing concentration. A negative relationship with FDI was
observed for inflation rate. (Chakrabarti, 2001;Woodward, Rolfe, 1993).
Agglomeration Theory
The theory of agglomeration economies inter-relates market
conditions. Agglomeration economies allow foreign firms to interact with
the community that they are located in. The geographical concentration
of foreign firms in a locality lowers the transaction costs in filling
up the labor requirements. Companies in the location find it easy to
hire workers through networking, word of mouth, local trade
publications, and referrals. These companies would have a ready supply
of workers who can be hired when needed. However, the labor market may
be volatile and seasonal, thus, workers may be hired only for a short
period. Workers also benefit since they can be readily hired in a big
labor market and improve their competencies and acquire skills as they
move from one job to another as a result of agglomeration economies.
(Scott 1998).
The clustering of companies in a particular area work both ways for
the companies and the available workforce. Companies in a geographical
concentration may have both backward and forward integration of firms
and economies of scales. This may serve as an incentive for foreign
firms to localize their activities in a particular area. (Pazienza,
Vecchione, 2009; Scott, Storper, 2003). This occurrence under
agglomeration economies brings a positive relationship to FDI since the
experience of one foreign company in the host country can be shared to
those intending to invest in that country. The Japanese FDI was cited as
particularly sensitive to agglomeration (Pazienza, Vecchione, 2009;
Zhou, Delios, Yang 2002).
METHODOLOGY
In 1992, the United States left Subic Bay naval base. Thus, RA 7227
also known as the Bases Conversion and Development Act of 1992 was
enacted. Republic Act (RA) 7227 directs that "Subic Bay
Metropolitan Authority (SBMA) shall promote and develop the Subic
Special Economic Zone into a self-sustaining, industrial, commercial,
financial and investment center to generate employment opportunities in
and around the zone and to attract and promote productive foreign
investments." (SOFA 2006).
We use data from SBMA for 2004-2008 to estimate the determinants of
FDI in Subic Bay Freeport Zone. The determinants were approved number of
projects, market size, degree of openness, infrastructure, labor
quality, labor costs, inflation, foreign exchange, taxes, revenue
collections, and exports.
The FDI in Subic Bay, the dependent variable, is represented by the
committed investments in US$. The committed investments are proposed
contributions by non-residents to various project undertakings in Subic
Bay. Market size is the Gross Domestic Product (GDP) per capita in US$.
(Chakrabarti, 2001). The degree of openness is the ratio of exports to
GDP (Li, Hou, and Chan, 2008). Exports data only cover those within
Subic Bay and thus do not include the whole country's exports data.
GDP refers to the country's GDP since there is no available GDP
data for Subic Bay. Infrastructure is captured by highways, where we
calculate the total kilometers of highways per square kilometer of land.
(Li, Hou, and Chan, 2008). To determine labor costs, we derived the
average minimum daily wage rate for the different sectors:
nonagricultural, agricultural, private hospitals, retail/service, and
cottage/ handicraft. Data on the daily wage rate for the different
sectors and exports are from SBMA. We also included data on the
available workforce to support labor quality. Data on taxes and cash and
non cash collections are from the Bureau of Internal Revenue (BIR) and
the Bureau of Customs (BOC), respectively. Inflation, foreign exchange
rates are gathered from the Bangko Sentral ng Pilipinas (BSP).
A multiple regression was initially employed:
[FDI.sub.t]= [[beta].sub.0] + [[beta].sub.1] [(MSIZE).sub.t] +
[[beta].sub.2] [(approved projects).sub.t] + [[beta].sub.3]
[(DEGOPEN).sub.t] + [[beta].sub.4] [(Labor cost).sub.t] + [[beta].sub.5]
[(Lab quality).sub.t] + [[beta].sub.6] [(Infras).sub.t] + [[beta].sub.7]
[(Infl).sub.t] + [[beta].sub.8][(Forex).sub.t] +
[[beta].sub.9][(BIR).sub.t] + [[beta].sub.10] [(BOC).sub.t] +
[[beta].sub.11][(Exp).sub.t] + [epsilon] (1)
Where MSIZE = market size
Approved projects = total number of approved projects
DEGOPEN = degree of openness
Labor cost = average minimum daily wages
Labor quality = available workforce
Infras = Infrastructure
Infl = Inflation
Forex = foreign exchange rate
BIR = taxes
BOC = cash and non-cash collection
Exp = exports
Table 1 offers a description of the variables used in the
regression model and the a priori expectations. Split regression was
eventually used as there were several years when one or more variables
were unobtainable. The 90% level of significance was used.
RESULTS
Correlation matrix shows the relationship between FDI, the
dependent variable with the independent variables. The following
variables have the highest correlation with FDI: Inflation at -73%, Cash
and non cash collection from the Bureau of Customs, 64%, followed by
average minimum wage at 51%, and approved number of projects, 47%. (see
Table 2)
Tables 3,4 and 5 show the relationship of FDI with the different
variables using split regression: market size, total number of approved
projects, degree of openness, infrastructure, labor costs and quality,
inflation, cash and non cash collections of BOC, taxes (BIR), and
foreign exchange rates. The rest of the variables have weak correlations
that may merit separate testing to determine the influence on investment
decisions.
At the 10% level of significance, all variables have positive r2.
FDI and market size represented by GDP per capita shows a positive
relationship. There is a weak correlation because the GDP is an
aggregate figure representing the country. This was used in the model
since there is no available data for GDP of Subic Bay. There may be
other variables that can influence the FDI in SBMA. Figure 1 presents
the committed investments were highest in 2007 but was affected by the
global financial crisis thus, there was a big decline in committed
investments in 2008.
[FIGURE 1 OMITTED]
FDI and total number of approved projects have a positive
relationship although it is statistically insignificant. There is a
41.8% probability that the coefficient is equal to zero. FDI will
increase by 0.02%. (Table 4). And for every 1% increase in approved
projects, FDI will increase by 0.39%. (Table 5).
Chakrabarti (2001) surveyed literature that presents a positive
relationship between FDI and degree of openness. Degree of openness is
the ratio of exports to GDP. While Table 3 shows that FDI and degree of
openness have a positive relationship, this relationship is not
significant. The same observations are shown in Tables 4 and 5. What we
can draw from here is that there is a degree of openness in SBMA since
the exporters come from foreign owned companies who are located in SBMA.
Figure 2 show exports increasing in the five-year period. However, the
degree of openness may not be enough to bring in foreign investors as
evidenced by the low level of significance. The NSCB fourth quarter of
2008 data showed that Subic Bay only had 0.4 billion pesos investments
which is only 0.54% of total approved FDI by IPAs.
[FIGURE 2 OMITTED]
There is a negative relationship between FDI and infrastructure.
There are two ways to go to Subic from Manila, both passing through the
North Luzon Expressway (NLEX). The SubicClark-Tarlac Expressways (SCTEX)
connects with NLEX to go straight to Subic.. SCTEX was opened in 2008.
The other way is via the old highway. Although, there are additional
highways, there is a lack of farm to market road access towards SCTEX.
Those who are near or along the highway but no inroads for agriculture
would rather go to the Manila port area than in Subic Bay to ship their
produce. The shipping costs are lower in the Manila port area because
there are more ship calls. In Subic Bay, there are only a few ship calls
which make shipping costs higher since there only a few cargos to ferry
out in the turn around. The r2=0.09 shows that the infrastructure has a
positive impact on FDI although the relationship is weak. However, he
new expressway is expected to attract more tourists, both local and
foreign since travel time between Subic and Clark has become shorter.
The average daily minimum wage for the different sectors ,
represented by labor costs has a positive relationship with FDI and has
a strong correlation, r2=0.55. The minimum daily wage increases at
average of 6.6% annually. Also, the available workforce shows a positive
relationship with FDI although the correlation is weak at r2=.2073.
Although the correlation is weak, Figure 3 shows that the available
workforce in Subic Bay is increasing every year at an average of 12%
yearly. The workforce includes skilled workers for manufacturing,
shipping, construction, household/ caretakers and services.
[FIGURE 3 OMITTED]
Both inflation and forex have negative relationships with FDIs.
Inflation would have an impact on the production cost of foreign firms
operating in SBMA. Also, foreign firms would want a stronger US$ versus
the local currency, the Philippine peso since this would make their
production costs lower.
The regression results with FDI and cash and non-cash collection
from the Bureau of Customs (BOC) show a positive relationship. The same
pattern can be seen for FDI and taxes collected by the Bureau of
Internal Revenue (BIR). Figure 4 shows that cash and non cash
collections of the Bureau of Customs (BOC) and taxes by BIR are
increasing. The situations that can affect these variables, cash
collections and non cash collections, and taxes are the effectiveness of
fiscal policy in Subic Bay and the political will. Although, there are
mixed conclusions in literature on the relationship of income tax
incentives and FDI. Woodward and Rolfe (1993) cited Rolfe and White
(1992) and Guisunger (1985) that income tax incentives have positive
relationship with export oriented FDI. However, Chakrabarti (2001)
presented literature that do not provide conclusive relationships
between FDI and tax incentives.
[FIGURE 4 OMITTED]
Agglomeration Theory
Agglomeration economies have a positive relationship to FDIs. With
more investors coming in from one country to the host country, there is
a tendency to be in close proximity to geographical clusters of
industries. (Pazienza, Vecchione, 2009; Zhou, Delios, Yang 2002). Table
6 shows the classification of companies by nationality from 2006-2008.
Filipino owned companies have the most in Subic Bay which maybe
considered as local investment, followed by Koreans. In the three years
span, all nationalities have increased the number of companies in Subic
Bay thus we can infer that they are in close proximity which makes it
easy to fill up the labor requirements.
In 2004-2007, half of the available workforce fall under the
services sector, followed by manufacturing at an average of 25%. In
2008, shipping and marine related industries contributed 35% of total
workforce. This sector came in second to services at 41% and 17%
manufacturing, third at 16% of the total 2008 available workforce of
87,502. Since there was intensive labor requirements for shipping and
marine related industries, there are some workers under services and
manufacturing on contractual basis that moved to the shipping and marine
related industries. Since the foreign firms are geographical
concentrated, it is easy for both employer and would be employee to
match and fill up openings. We can infer that agglomeration economies
exist in Subic Bay since the number of foreign firms coming from one
country increases, thus increasing foreign direct investments.
Competition
Investment Promotional Agencies (IPAs)
The following are the IPAs in the Philippines: Board of Investments
(BOI), Philippine Economic Zone Authority (PEZA), Clark Development
Corporation (CDC) and Subic Bay Metropolitan Authority (SBMA). The 2008
annual FDI reached PhP 182.7 billion, lower by 14.7 percent than the PhP
214.1 billion approved in 2007. Electricity and manufacturing remained
the top industries for FDIs in 2008, while finance and real estate and
private services dominated the last quarter of 2008. The major sources
of FDI commitments are Netherlands (24.8%) at Php45.4 billion and Korea,
with a share of 21.9 percent or PhP40.0 billion in 2008. The United
Kingdom and United States of America had 13.8 percent and 10.8 percent
or PhP 25.3 billion and PhP 19.7 billion worth of investments,
respectively. Among the country's four major IPAs, BOI got more
than half of the total approved FDI in 2008 (51.2%) or PhP 93.6 billion.
The rest of the FDI for 2008 are distributed to the following IPAs: PEZa
(38.5%) or PhP 70.4 billion, SBMA and CDC with combined PhP 18.8 billion
worth of investments or 10.3% .(http://nscb.gov.ph)
Majority of foreign and Filipino investments for fourth quarter
2008 went to BOI and PEZA. PEZA had Php60.4 billion or 81.7 percent
possible investments, BOI (17.4%) had Php12.9 billion investment
pledges. SBMA (0.54%) only had Php0.4 billion, which was a 196% decline
from Php9.3 billion investment in the fourth quarter in 2007. CDC
(0.27%) also decreased by 180% from Php1.0 billion to Php0.2 billion.
(http://nscb.gov.ph)
Foreign Competitors
UNCTAD's World Investments Prospect Survey 2009-2011 showed
that BRIC (Brazil, the Russian Federation, India and China) tops the
list of most favored location for FDIs. China ranked first and India
third. The leading determinants influencing location of companies are
size of local market, market growth, presence of suppliers/ partners,
access to international/regional markets, stable and friendly business
environment, availability of cheap labor, access to natural resource.
In 2008, the inward FDI of China amounted to US$108,312 million
which was a 240% increase from 1990. There was also a 22% increase from
2007 FDI of US$83,521 million. While, the inward FDI of India for 2008
amounted to US$33,033 million which was a 72% increase from 2007
US$19,156 million. (http://www.unctad.org/Templates/ Page.asp?intItemID
=2441&lang=1; http://dipp.nic.in/fdi_statistics/india_FDI_December2008.pdf
Vietnam has established a total of 154 Industrial Zones and export
processing zones (EPZs). For 2008, total approved FDI was US$64 billion.
As of November 2007, there were 2,627 foreign invested enterprises
licensed in the zones with a total registered capital of $25.5 billion.
As of August 2007, the number of on-going projects is 7,833 with
investors coming from 79 economies. The emergence of Vietnam as a
location for possible investments from Taiwan affected Subic Bay. (SOFA
2006).
The Philippines total approved FDI was only US$4,107 million in
2008 which is a measly 4% of China's FDIs. Comparing with India and
Vietnam, the Philippine's FDI was 12% and 14% of their total FDIs,
respectively. The Philippines is only getting a small portion of
possible FDIs and may need to review its investment policies.
Also, China has minimal FDI in the Philippines. China is estimated
to have GDP growth rate of 7.5%, in 2010. At present, the manufacturing
sector from China's FDI to the Philippines dominates. However, this
is minimal and the Philippines can strategize in tapping FDI from big
companies established under the central government. (SBMA, 2008).
CONCLUSIONS
Based on the regression results, the following determinants have
positive relationship with FDI: market size, total number of approved
projects, degree of openness, labor costs and labor quality, and
exports. FDI has a positive relationship with cash and non-cash
collection (BOC), taxes which is contrary to a priori expectations but
is supported by other literature. The number of approved projects,
average minimum daily wage, and cash and non-cash collections by the
Bureau of Customs have shown strong relationships. The following have
negative relationship with FDI: forex, inflation, infrastructure.
Investors or locators consider Subic Bay because of a perceived
easy living where amenities are readily available. Also, since the
available workforce has the skills and competencies, which can make them
readily adapt to changes, they are marketable and can readily be
employed. The geographical concentration of companies in one location
provides economies of scales. The number of companies by nationality
increases over the years. We can infer that agglomeration economies
exist in Subic Bay and have positive relationships with FDIs.
RECOMMENDATIONS
Since there was a decline in FDIs in 2008 due to the global
financial crisis, IPAs have relaxed/ modified regulations or policies,
more incentives, additional inclusions to tax and duty free importation,
streamlined procedures. (SOFA 2008). IPAs are doing international road
shows to promote the Philippines and get more FDIs.
SBMA must continue to take initiatives in adopting more investment
policies that can compete with other countries. They can look at other
countries IPAs and adopt best practices and create a one stop shop
business for the locators.
In the midst of the global financial crisis, SBMA must rethink on
how it would be able to get more FDIs, since it is competing with the
local IPAs and other countries. They can review its global
competitiveness by doing a self-assessment and benchmarking with these
IPAs and the top three leading in FDIs, China, India, Vietnam. A survey
can also be done for the locators or investors in Subic Bay. The survey
can be done in several phases, tapping the different sectors to better
understand the motivation of doing business in Subic Bay. The results
can be used as inputs for the strategic plans of SBMA in increasing its
FDIs.
With the opening of the SCTEX, SBMA can work with CDC by tapping
flights from Clark. This could open more opportunities for a complete
cost competitive package for tourist destinations, ecotourism, diving,
beach.
SBMA can envision a long-term plan to have a community development
intended for retirees that would be complete with housing, recreational
activities, medical facilities. Also, since there are international and
local schools in Subic Bay, this would provide world class education to
the dependents of the locators. The locators can also work with the
schools in providing on the job training in order to provide minimum
competencies for those who will work in the different sectors in Subic
Bay Freeport
There is a need to further improve the infrastructure,
telecommunications, utilities support that they offer to investors. SBMA
must compare the prices with other local and foreign IPAs for cost
efficiency so that they will be able to have more locators in Subic Bay.
Also, there is a need to upgrade telecommunications for the planned
Business Processing Outsourcing and Information Computer Technology hub
project with Clark.
There is a need for more farm to market access roads which will
help increase the cargo that would be shipped and the costs will be
lower. Perhaps, it is possible to make representations with different
government representatives on how there will be road accessibility from
the various areas near Subic Bay. This will encourage the locals and
nearby provinces to use Subic Bay for their shipment requirements rather
than go to Manila.
Since there was data constraint on running the regression model, it
is recommended that the different units working in SBMA have a database
that can easily be retrieved and be used for strategic planning. As
such, the regression model used in the study can have more years, other
variables, and include the other IPAs and other countries to validate
the results of the model.
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Leila Y. Calderon-Kabigting, De La Salle University
Table 1: Specification of Variables Used in the Model
VARIABLES Description A priori
expectation
FDI (dependent Committed
variable) investments in SBMA
Market size GDP per capita positive
Degree of openness Exports in SBMA/GDP positive
Infrastructure Total kilometers of positive
highway per square
kilometer of land
Average minimum Average minimum positive
Wage (labor costs) daily for different
sectors:
Non-agricultural,
agricultural
Private hospitals,
retail/service, And
cottage/handicraft
Labor quality available workforce positive
in SBMA
Exports Exports from SBMA positive
Inflation Inflation data (BSP) negative
Foreign exchange Foreign exchange negative
rate rate (BSP)
Taxes (BIR) Taxes negative
Revenues ((BOC) Cash and non-cash negative
collections
Table 2: Correlation Matrix
committed approved market
investments projects size
(Fdi)
committed 1
investments (Fdi)
approved projects 0.475296897 1
market size 0.3604362 0.880141332 1
degree open 0.452108137 0.534318803 0.7579401
infrastructure -0.307394492 0.597597894 0.745401112
available workforce 0.184290874 0.848075473 0.982699514
ave min daily wage 0.515339206 0.889189638 0.966074439
forex -0.46388222 -0.918356851 -0.990082169
inflation -0.737704966 -0.165372647 0.10204782
boc 0.639438893 0.182597721 0.198669697
bir 0.426930958 0.856899248 0.993258402
exports 0.188479609 0.850248963 0.810990964
degree infrastructure available
open workforce
committed
investments (Fdi)
approved projects
market size
degree open 1
infrastructure 0.521804401 1
available workforce 0.692594986 0.845779744 1
ave min daily wage 0.851877123 0.653705608 0.915296463
forex -0.723212613 -0.661689758 -0.954591231
inflation 0.255855177 0.672276839 0.238035373
boc 0.716071292 -0.081925989 0.06942262
bir 0.76270713 0.674319795 0.961134032
exports 0.235259317 0.605811251 0.833328423
ave min forex inflation
daily wage
committed
investments (Fdi)
approved projects
market size
degree open
infrastructure
available workforce
ave min daily wage 1
forex -0.968584714 1
inflation 0.034243391 0.03547568 1
boc 0.433262075 -0.2146937 -0.0732977
bir 0.960633954 -0.9907815 0.0289811
exports 0.686070542 -0.8356722 -0.1352341
boc bir exports
committed
investments (Fdi)
approved projects
market size
degree open
infrastructure
available workforce
ave min daily wage
forex
inflation
boc 1
bir 0.2134602 1
exports -0.3176469 0.8004838 1
Table 3: Split Regression Results of FDI with the
Independent Variables
Dependent Variable: FDI
VARIABLES coefficient p-value [r.sup.2]
Market size 873312.78 0.551 0.1299
Total number of approved 7987094 0.418 0.2259
project
Degree of openness 14528764.73 0.445 0.2044
Infrastructure -3.94e+07 0.615 0.0945
Average minimum wage 15187639 0.374 0.2657
Available workforce 11557.82 0.767 0.0340
Exports 1.100469 0.761 0.0355
Foreign exchange rate -7.17e+07 0.431 0.2151
Inflation -2.45e+08 0.155 0.5442
Cash and non cash 35.02951 0.245 0.4089
collections (BOC)
Taxes (BIR) 41.47316 0.473 0.4873
Table 4: Split Regression Results of lnFDI with the
Independent Variables
Dependent Variable: FDI
VARIABLES coefficient p-value [r.sup.2]
Market size 0.003139 0.322 0.3186
Total number of approved .027079 0.186 0.4930
projects
Degree of openness .0453 0.270 0.3777
Infrastructure -.0010153 0.996 0.0000
Average minimum wage 0.049039 0.166 0.5257
Available workforce .0000597 0.488 0.1719
Exports 4.55E-09 0.576 0.1151
Foreign exchange rate -.2302573 0.236 0.4214
Inflation -.4146489 0.344 0.2953
Cash and non cash 8.78e-08 0.190 0.4873
collections (BOC)
Taxes (BIR) 1.33e-07 0.288 0.3557
Table 5: Split Regression Results of lnFDI with the LN
Independent Variables
Dependent Variable: FDI
VARIABLE coefficient p-value [r.sup.2]
LNMarket size 3.587019 0.277 0.3689
LNTotal number of approved .395417 0.150 0.5519
projects
LNDegree of openness 6.31457064 0.272 0.3747
LNInfrastructure -.0183836 0.996 0.0000
LNAverage minimum wage 12.30736 0.152 0.5494
LNAvailable workforce 4.638253 0.441 0.2073
LNExports 3.568504 0.601 0.1015
LNForeign exchange rate -11.23047 0.252 0.3997
LNInflation -2.355748 0.300 0.3426
LNCash and non cash 8.556389 0.170 0.5190
collections (BOC)
LNTaxes (BIR) 3.022733 0.251 0.4011
Table 6: Subic Bay Freeport Classification of Companies
by Nationality
As of As of As of
Nationality June 2006 Sept 2007 June 2008
American 29.84 30.36 33.46
British 14.16 13.11 12.94
Dutch 1.25 1.25 2.5
Filipino 393.89 433.55 486.53
Hong Kong 1.5 1.5 1.5
Korean 28.96 71.17 108.55
Japanese 33.96 34.05 40.42
Singaporean 3 3.08 3.08
Taiwanese 48.39 56.71 58.58
Swiss 2.12 2.62 2.62
Others 25.93 31.69 38.23
Total 583 679.09 788.41
Figure 5: 2008 Available Workforce by Sector
2008 Active Workforce by Sector
Manufacturing 17%
Services 41%
Shipping/ Marine related services 35%
Construction 6%
Domestic Helpers/ Caretakers 1%
Source: SBMA State of the Freeport Address (SOFA) for 2008
Note: Table made from pie chart
