International business review volume 15 issue 4 2006 doi 10 1016 j ibusrev 2006 05 001 hussain gulzar rammal; ralf zurbruegg the impact of regulatory quality on intra foreign direct investment

international
business
review
International Business Review 15 (2006) 401–414
The impact of regulatory quality on intra-foreign
direct investment flows in the ASEAN markets
Hussain Gulzar Rammal
Ã
, Ralf Zurbruegg
The University of Adelaide, School of Commerce, 233 North Terrace, Adelaide 5005, Australia
Received 7 June 2005; received in revised form 17 December 2005; accepted 3 May 2006
Abstract
Using a panel data set containing information on FDI flows from home to host countries, this
paper examines the impact of changes in the quality of government regulatory effectiveness and
governance practices upon the direction of outward FDI flows between five ASEAN economies of
Indonesia, Malaysia, Philippines, Singapore, and Thailand. The results show that a deterioration in
the effectiveness and enforcement of investment regulations (such as price controls and excessive
regulation in foreign trade and business development) have an adverse effect upon intra-ASEAN
FDI, and are significant factors in explaining the recent downward trend in ASEAN FDI flows.
These results are robust to changes in a number of controlling variables for various economic
conditions that the extant FDI literature consider. Also, these results have several significant
implications for future policy makers in recommending means to revitalize intra-ASEAN investment.
r 2006 Elsevier Ltd. All rights reserved.
Keywords: Foreign direct investment policy; Investment incentives; Intra-ASEAN FDI
1. Introduction
The Asian financial crisis in 1997 was viewed by many as an opportunity for the Asian
nations to initiate and implement regulatory and institutional reforms that would increase
investor confidence, resulting in increased FDI activity (Bremner, Thornton, Prasso, &
Foust, 1997; Hornick, 1997; Magnusson, 1997). But recent statistics have revealed that
outward FDI from ASEAN markets to other ASEAN neighbors ha s stagnated. Several
commentators have inferred that this may be due to under-developed regulatory and

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Ã
Corresponding author.
corporate governance practices that have not been strengthened since the 1997 crisis.
Huang, Morck, and Yeung (2004), in particularly, argue that poor institutional
environments within some of the ASEAN nations can expose them to further external
shocks that may divert FDI away from these countries. Given the reliance of some of these
ASEAN countries on FDI, especially from China and Japan, the economic consequences
can be quite dramatic. Moreover, with the growth of more economic trading blocks, such
as FTAA in the Americas and EU expansion into central and Eastern Europe, the
competition for FDI will inevitably increase within these ASEAN markets.
Separate to the issue of diminishing FDI from non-ASEAN countries, is the drop in
outward FDI from ASEAN countries to its fellow member states. Despite geographic
proximity, in many ASEAN countries outward FDI to member states has not returned to
pre-1997 levels (ASEAN, 2004). Although this may in part be due to several economic
factors, where some states have not fully recovered from the effects of the 1997 crisis, it
may also be in part due to the slow pace of governance reform that has taken place since
1997. With emerging markets in other areas of the world opening up potentially more
profitable opportunities, ASEAN FDI within its own borders may have been dampened by
lack of reforming institutional commercial practices that would encourage intra-FDI
flows.
This paper considers whether governance reforms implemented via regulations influence
outward FDI between five ASEAN markets of Indonesia, Malaysia, Philippines,
Singapore, and Thailand. Sections 2 and 3 provide an overview of the existing literature,
followed by a discussion of the data used and model utilized to examine the significance of
regulatory governance upon outward FDI flows. This is accompanied, in Section 4, with
the empirical results before a conclusion and policy implications are presented in Section 5.

2. Literature review
The 1990s witnessed a change in the geographical pa tterns of FDI outflows. Europe and
North America maintained their position as the largest source of FDI flows in the world
(Pangarkar & Lim, 2003). However, from 1998, Asia’s share of total FDI fell due to the
declining role of Japan as a FDI supplier. Inward FDI into the Asian economies was also
affected, post-Asian crisis. Also, within the East-Asian economies, Malaysia, Thailand,
and Philippines were no longer the favored FDI destinations of MNCs (Brooks & Hill,
2004). To reverse this trend, governments of ASEAN nations started focusing on
macroeconomic reforms (Soesastro, 1998) that would again promote investment and FDI
in their own countries. For example, Singapore’s response to the Asian crisis involved
undertaking a range of internal reforms and restructuring aimed at improving
international competitiveness (Chia, 1998). Malaysia’s response was aimed at reforming
its banking systems (Athukorala 1998), while Thailand and Indonesia focused on
implementing political, institutional, and regulatory reforms (Chowdhury, 1999; Thomp-
son & Poon, 2000). Despite these changes, FDI statistics indicate that these reforms have
failed to improve FDI levels in the ASEAN region (ASEAN, 2004). This brings into
question the effectiveness of these reforms to begin with, specifically if they were directly
dealing with means to promote overseas investment. In particular, were corporate
governance and regulatory frameworks adequately improved to restore lost investor
confidence after the 1997 Asian financial crisis? For ASEAN, this is a particularly pertinent
question. In particular, growth of intra-FDI trade cannot be ignored, as in part it signals
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H.G. Rammal, R. Zurbruegg / International Business Review 15 (2006) 401–414402
the effectiveness of an economic trading block and is one of the main purpose of ASEAN’s
existence (Severino, 2000). Without growth in trade within its own borders, the economic
value of actually being an ASEAN member diminishes.
The extant literature on the impact of the political and legal environment upon the
economy has shown, repeatedly, that good corporate governance leads to increased
economic growth. Laporta, Lopez-de-Silanes, Shleifer, and Vishny (1997, 1998, 2000)
examine the importance of national legal origin on creditor and shareholder rights, along

with the implications of creditor and shareholder rights, and legal enforcement on external
finance. Levine (1998, 1999), Beck, Levine, and Loayza (2000) and Levine, Loayza, and
Beck (2000) extend this research to examine the importance of legal systems for economic
growth and financial development. An important conclusion is that countries with poor
legal rules and law enforcement have narrower debt and equity markets (LaPorta et al.,
1997), and that a well-defined and enforced legal system facilitates greater financial
intermediation, and thereby economic growth (see Levine et al., 2000).
To focus more closely on FDI research, work by authors such as Carstensen and Toubal
(2004), Nonnenberg and Mendonca (2004) and Janicki and Wunnana (2004) have all
highlighted the significance of country risk as a determining factor for encouraging FDI in
developing countries. Moreover, research by Hellman, Jones, and Kaufm ann (2003) show
that in fact FDI inflows can also help improve standards of governance in transition
economies, implying that there is a two-way causality effect between governance standards
and FDI. As an economic trading zone, FDI also takes on a significant meaning in
signaling not only the economic, but also political ties ASEAN members will have with
each other.
The literature to date, however, on FDI flows within and between ASEAN countries is
comparatively restricted, despite the growing economic importance of the South-East
Asian region. To partially rectify this lack of research, this paper examines a particular
component of ASEAN trade, that of examining whether intra-ASEAN FDI is also
significantly affected by institutional factors relating to regulatory quality (RQ) and
effectiveness that influences the ease by which FDI can enter a country. Given the close
proximity of each of the ASEAN nations, in terms of both cultural and geopolitical
factors, the importance of regulatory effectiven ess and governance standards cannot be
ignored for MNC’s choice of direct foreign investment within these countries. In fact, it
would further highlight the need for ASEAN to address not only economic, but also legal
and political institutional matters if it is to grow further as a tradi ng zone.
3. Data and research method
The dataset used to determine the importance of regulatory matters upon intra-ASEAN
FDI flows originates from several different sources. The data for the primary variable of

this paper, that being outward bound FDI flows from ASEAN countries, was obtaine d
from the ASEAN Finance and Macroeconomic Surveillance Unit (FMSU) database
(ASEAN, 2005). Annual figures were obtained for the five countries between 1996 and
2002. Only five of the ASEAN states had a complete set of results for this time period and
therefore precluded the addition of further countries to this study.
Along with data for the above dependent variable, a number of explanatory variables
need also to be considered in order to determine their importance in influ encing FDI flows.
There are, in fact, a host of potential explanatory variables that could be collated and used
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H.G. Rammal, R. Zurbruegg / International Business Review 15 (2006) 401–414 403
to determine FDI movements. In particular, the literature covered in the previous section
highlighted the potential importance of country risk and the possibility of institutional
political and legal factors in this context. The impact of regulation, for example, on FDI is
demonstrated by the United Nations Conference on Trade and Development (UNCTAD)
(1998) World Investment Report, which concluded that in developing countries policy
changes aimed at creating more favorable conditions for FDI had not only led to more
liberal trade and investment policies, but also improved general economic conditions,
making these countries a more conducive and accommodating environment for FDI inflow
(Fan & Dickie, 2000). Sethi, Guisinger, Ford Jr., and Phelan (2002) refer to these
regulations as ‘Pull’ factors (institutional factors).
In this study, a specific measure for RQ and effectiveness is used. The data was obtained
from earlier work conducted by Kaufmann, Kraay, and Mastruzzi (2004) as part of a
World Bank project. The Kaufmann, Kraay, and Mastruzzi (2004) study measured the
perception of governance using various tools, with the data being drawn from 25 separate
sources and constructed by 18 different organizations across a wide range of countries.
One of the variables they created was RQ, referring to the incidence of market-unfriendly
policies such as price controls or inadequate financial supervi sion, as well as perceptions of
the burdens imposed by excessive regulation in areas such as foreign trade and business
development. Overall, it provides a measure for a specific aspect of corporate governance
that would have a significant bearing on the ease by which foreign firms could directly

invest in a host market. It is for this reason that RQ is chosen as the principal tool to
determine whether RQ and effectiveness significantly influences intra-ASEAN FDI trade.
The RQ indicator is measured in units ranging from about À2.5 to 2.5, with higher values
corresponding to better governance outcomes.
Apart from using RQ as a means to determine the significance of RQ and effectiveness
in influencing FDI flows, it is also necessary to incorporate a number of controlling
variables into the model. This would allow for the model to account for such issues as the
impact of adverse economic conditions upon general foreign investment into a country.
Kyrkilis and Pant elidis (2003) argue that macroeconomic characteristics such as income,
exchange rate, technology, human capital, and openness of the economy all have a
significant impact on outward FDI positions for countries.
For this study, a selection of control variables that are regularly used in the FDI
literature is applied. Specifically, four macroeconomic variables were also extracted from
the FMSU database (ASEAN, 2005). These include a measure of economic activity
(annual GDP per capita), economic growth (change in GDP year on year), annual inflation
rates (measured as a function of the local consumer price index), and an annual measure of
the risk-free rate of return (interest on 3-month time deposits). The first two measures
relate directly to the size and health of an economy, and one would expect a positive
relationship to emerge between them and increasing FDI. The relationship that exists
between inflation rates plus interest rates with FDI is not so clear cut, though it would
generally be argued that higher inflation and interest rates would be a disincentive to invest
in a country. As the relative cost of borrowing and those costs associated with operating in
an inflationary environment would diminish the opportunity costs from investing in the
economy.
Along with the above macroeconomic variables, a selection of more finance-based
factors were also collected from the World Bank’s (2005) financial development and
structure database. As a means of providing a basic robustness test for the empirical results
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H.G. Rammal, R. Zurbruegg / International Business Review 15 (2006) 401–414404
that will be presented, two separate sets of control variables are utilized. Doing so will

provide a means to determine whether any results that indicate the significance and
importance of RQ in influencing outbound FDI is not wholly sensitive to the choice of
control variables accompanying the model.
The extra variables chosen are total stock turnover (ST) and liabilities (L). ST is a ratio
of the value of total shares traded over average real market capitalizati on for any
particular year. As a ratio, it provides a measure for how active the financial market is in a
host country. It can provide an indirect measure for the activity within the economy, which
may encourage FDI. The second variable, L, is a ratio measuring liquid L to GDP. The
greater amount of liquid L within a market, the more constrained it may be to grow.
However, it could also represent willingness to accumulate debt as a means to invest .
Therefore, it could also be interpreted as a positive signal to investors. The relationship it
would therefore share with FDI flows would also be dependent on the level of interest rates
within an economy, where higher interest rates would imply a greater cost on the economy
for having a significant amount of L outstanding. Its importance in influencing FDI flows,
however, cannot be ignored as a basic measure of debt within the economy.
To provide the robustness test in determining the impact of RQ upon outbound FDI,
two separate series of regressions were run for each country. A total of ten regressions are
presented in the empirical section, where each country’s FDI to the other four countries in
the sample were regressed against a set of control variables plus RQ. As there are four
series (countries) of outward FDI for each regression, a panel dataset was created.
With regard to the particular econometric model applied, the majority of quantitative
research that have previously examined the determinants of FDI utilize either a cross-
country or pooled data approach to modelin g. Although cross-country analysis is useful
for providing averages across a large cross-section of countries, this paper adopted the
latter method. Given that there is only limited data for intra-FDI flows within ASEAN it is
important to make use of the temporal dimens ion of the dataset to increase the degrees of
freedom within the model. Also, pa nel data modeling can explicitly account for within-
country variability across time (see Islam (1995) and Folster and Henrekson (2001)), which
is an important factor for this particular dataset, given the changes to trade openness and
the impact of the 1997 financial crisis has had on the ASEAN countries. Therefore, the two

sets of empirical results presented in the following section follow a standard panel mod el
specification, given as
y
i;t
¼ bx
i;t
þ v
i;t
; i ¼ 1; N; t ¼ 1; ; T, (1)
where y is the dependent variable, FDI, and x being a set of explanatory variables over
time, t, and between countries, i. The term v
i,t
captures the stochastic component of the
data with v
i;t
¼ a
i
þ u
i;t
where a
i
represents the country effect for which a
i
$ð0; s
2
a
Þ and u
i,t
is
a stochastic disturbance such that u

i;t
$ð0; s
2
u
Þ. The model is estimated using generalized
least squares.
Given the restrictive nature of the data (in terms of degrees of freedom), only results
obtained from a fixed-effects model is presented. This implies there is an assumption that
there is within- group variation, where the differences among countries are captured by
allowing for a different intercept, a
i
, for each country included within the regression. The
alternative to this is to run with a random effects model, implying country effects are
randomly distributed and unobservable. The latter option is not very common, but in this
study’s case it is also not possible to feasibly examine, as it requires a larger cross-section of
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H.G. Rammal, R. Zurbruegg / International Business Review 15 (2006) 401–414 405
countries than is available. In fact, there needs to be a greater number of countries in the
sample than independent variables, which is not the case for the model presented in this
paper. One of the limitations of this study is the lack of usable data. To an extent, it in fact
precluded previous econometric research in this area, as a sufficient time series for a
minimal number of countries was simply not available.
4. Empirical results
Focusing the attention on the descriptive statistics presented in Table 1, a number of
stylized facts emerge. First, they show that there exists a huge gap in the GDP per capita
among the ASEAN nations that are in the sample. Singapore’s GDP per capita for the
period studied was US $22,873.43. In comparison, the other four ASEAN nations had a
far lower GDP. Malaysia’s per capita GDP was $4,060.71, Thailand’s was $2383.71,
Philippines’ was $1034.71, and Indonesia’s GDP per capita was $851.71.
The economic growth rate has been low for the five ASEAN nations ov er the sample

period compared to growth ach ieved in the early to mid-1990s. Singapore’s growth rate is
the highest at 5.15%, followed by Malaysia (4.97%), Philippines (4.02%), Indonesia
(2.27%), and Thailand (1.5 4%). The results in Table 1 also show that Indonesia has the
highest inflation and interest rates. In comparison, the other four nations seem to have
these economic variables under control. Malaysia has the highest L ratio, followed by
Singapore, Thailand, Philippines, and Indo nesia. The result for ST shows that Malaysia
has the highest ratio, followed by Singapore, Philippines, Thailand, and Indonesia. The
RQ scores reveal that Indonesia is the only country with an overall negative score.
Singapore has the highest score for RQ, while Malaysia, Philippines, and Thailand have
very similar scores.
Focusing a little more on the two primary variables of interest, FDI and RQ, Table 2
shows their scores prior to, and post the 1997 Asian crisis. This provides a basic picture for
how the performances of these two variables have behaved over the course of the sample
period. Scores reveal that with the exception of the Philippines and Thailand, which have
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Table 1
Descriptive statistics for the control parameters and regulation quality
Indonesia Malaysia Philippines Singapore Thailand
Mean Std. dev. Mean Std. dev. Mean Std. dev. Mean Std. dev. Mean Std. dev.
Economic activity ($US) 851.71 264.87 4060.71 629.65 1034.71 111.39 22873.43 2210.89 2383.71 544.75
Economic growth 2.27 7.19 4.97 6.34 4.02 2.18 5.15 4.73 1.54 5.87
Inflation rate 18.20 26.35 2.81 1.36 6.69 2.11 0.97 1.45 3.49 2.59
Interest rate 22.27 13.79 5.35 2.44 10.26 2.05 2.29 1.18 5.83 3.52
Liabilities 0.51 0.04 1.20 0.11 0.60 0.05 1.13 0.04 1.00 0.16
Stock turnover 0.20 0.10 1.79 0.56 0.59 0.15 1.49 0.21 0.43 0.22
Regulation quality À0.06 0.24 0.48 0.20 0.44 0.19 1.79 0.38 0.41 0.15
The sample consists of annual data extending from 1996 to 2002. Economic activity is measured as GDP in $US.
Economic growth, the inflation rate and interest rates are measured in percentage terms, with economic growth
being expressed as a logarithmic growth rate of the underlying annual change in GDP. The inflation rate is the
annual change in the consumer price index and interest rates are taken from 3-month treasury deposit notes.

H.G. Rammal, R. Zurbruegg / International Business Review 15 (2006) 401–414406
shown a slight improvement, the other three nations have actual ly shown deterioration in
the quality of regulations in the post-Asian crisis period.
The Asian crisis also affected the level of outward FDI within the five ASEAN nations.
Table 2 shows that the amount of FDI has in fact dramatically decreased, with Malaysia
and Thailand the worst hit. The negative score for Thailand indicates disinvestments, post-
Asian crisis.
The pr inciple results for the panel data models are presented in Tables 3 and 4. They
both tabulate results for individual regressions on each country’s level of outbound FDI
flows to the other four countries in the sample. Both Tables 3 and 4 also include the level of
foreign RQ as an explanatory variable, measur ing RQ and effectiveness in the market that
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Table 2
Change in the regulation quality index and outward FDI prior to and after the 1997 Asian economic crisis
RQ index Indonesia Malaysia Philippines Singapore Thailand
1996–1997 0.17 0.67 0.44 1.88 0.35
1998–2001 À0.18 0.39 0.44 1.75 0.44
Outward FDI
1996–1997 68.42 101.90 10.88 538.72 72.83
1998–2001 26.42 10.04 5.46 240.70 À0.47
Figures represent average annual figures. Outward FDI represents the total US$ value of all FDI originating for
one particular country to the other four countries in the sample.
Table 3
Panel regression results for determining outward FDI
Indonesia Malaysia Philippines Singapore Thailand
Host country economic activity À15.1303 À532.4027 72.8967 À1566.8590 138.3981
a
(35.4193) (350.5989) (84.9931) (1218.6420) (80.7362)
Host country inflation rate À0.4444 À3.6217
b

0.5206 À9.8833 0.2584
(0.8329) (1.6418) (0.6128) (10.8755) (0.6227)
Host country regulation quality 38.4591
c
16.7268 70.0155
a
1207.3591
b
139.5873
b
(12.2372) (101.8816) (36.5156) (585.9297) (58.3517)
Home country economic activity 24.5490 725.2806
b
À129.5480 2731.2314 130.6264
(26.5768) (365.0416) (150.3433) (2936.7828) (194.9942)
Home country inflation rate 0.1700 29.6635 1.4800 93.4541 2.0240
(0.1135) (30.3218) (4.7884) (177.2969) (4.8675)
Home country regulation quality 17.3086
a
172.7273 À63.4494 À611.0538 12.9934
(9.5804) (269.8804) (44.8762) (438.5181) (60.9409)
F-statistic 2.1415
a
2.9444
b
2.3262
a
2.9493
b
15.3439

c
Adjusted R
2
0.4333 0.5007 0.5139 0.5129 0.6993
All coefficient estimates are from a fixed-effects panel regression of outward FDI from the specified country to the
remaining four countries in the sample. Each regression is run from a balanced panel dataset consisting of 24
observations over four cross-sections (countries). Economic activity is measured as the logarithm of GDP in $US.
Weighted cross-sections are utilized and figures in brackets are White heteroscedastic-corrected standard errors.
a
Represents significance at the 10% critical level.
b
Represents significance at the 5% critical level.
c
Represents significance at the 1% critical level.
H.G. Rammal, R. Zurbruegg / International Business Review 15 (2006) 401–414 407
the FDI is flowing to. The tables do differ, however, in the set of control variables utilized
within each of the regressions. To start with, in Table 3 the model incorporates both home
and host country RQ, plus both home and host inflation rates, and level of economic
activity (measured as the logarithm of GDP).
The reason for the inclusion of both home and host values for inflation, GDP and RQ is
to consider the possibility that a multinational enterprise’s decision to invest abroad is
partially determined by the difference in opportunity cost of investing in their home
market, as opposed to a host market. This may also lead to a situation whereby a company
would prefer to invest in a neighboring country because its home market’s level of
corporate governance processes and RQ makes doing business in its own market too
difficult relative to outside investment. Therefore, to account for this fact, the role of both
home and host economic and regulatory factors are considered in this context of
determining whether only the host and/or source country plays a role in determining a
company’s decision to invest abroad.
The results for Table 3 are intriguing. The first noticeable point is that there is not a

consistent macroeconomic factor determining outward FDI for any of the five countries
examined. Partly, this may be due to the use of a small sample (there are 24 observations
for each regression), potentially limiting the ability of the model to pick up significant
economic relationships. However, one would still expect the most predominant economic
variables showing a degree of significance. It could very well be that due to the diverse
reactions the different countries took to handling the 1997 crisis, the economic variables
that are examined have all had a different impact on FDI flows between the cou ntries
leading to no single factor being significant in all the markets.
The level of host economic activity in determining the level of FDI is only significant (at
the 5% critical level) for one country, Thailand. The value of exami ning local GDP is also
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Table 4
Alternative panel regression results for determining outward FDI
Indonesia Malaysia Philippines Singapore Thailand
Host country 32.3377
a
À63.2806 À92.4535 1335.4690 À450.8577
Liabilities (14.7015) (163.5082) (89.6580) (1916.8550) (423.0489)
Host country stock 3.0945 À121.1778 À21.1862 318.8258 À129.0381
turnover (4.0262) (158.5455) (28.3477) (350.7438) (99.7615)
Host country 37.3771
b
29.0687 63.2648
a
235.5398
a
90.7115
a
Regulation quality (6.6949) (35.5620) (30.0718) (94.9261) (36.0515)
Host country interest 3.2215

b
2.5888
a
À0.7813 18.2052
b
1.9889
Rate (0.6823) (1.1690) (1.4129) (5.9848) (1.4493)
Host country 0.3243
c
4.8885
c
À0.2329 28.9248
a
6.0538
a
Economic growth (0.1845) (2.7882) (1.4775) (11.6965) (2.9628)
F-statistic 3.8384
a
1.5938 1.8495 5.7714
b
3.0401
a
Adjusted R
2
0.5058 0.2982 0.3813 0.6061 0.4833
All coefficient estimates are from a fixed-effects panel regression of outward FDI from the specified country to the
remaining four countries in the sample. Each regression is run from a balanced panel dataset consisting of 24
observations over four cross-sections (countries). Economic activity is measured as the logarithm of GDP in $US.
Weighted cross-sections are utilized and figures in brackets are White heteroscedastic-corrected standard errors.
a

Represents significance at the 5% critical level.
b
Represents significance at the 1% critical level.
c
Represents significance at the 10% critical level.
H.G. Rammal, R. Zurbruegg / International Business Review 15 (2006) 401–414408
only significant in one country, Malaysia. The importance of the host inflation rate as a
determinant of outward FDI is also not strongly supported, with it only being significant
for one country, Malaysia. The negative relationship shows that an increase in the inflation
rate lessens FDI in that country. For the home inflation rate, none of the results are
significant. Overall, these results are not particularly strong in outlining any particular
macroeconomic factor that drives outbound FDI for this period of study.
Finally, with regard to regulation quality, RQ, it is by far the most representative
significant variable within Table 3. The quality of host regulation guides and assessment is
a significant factor in determining FDI for three of the five countries. Only for Malaysia
and Thailand is no significant relationship found. In fact, it is only for Malaysia that
neither home nor host RQ is significant in influencing the level and direction of outbound
FDI. This may be partially due to the fact that Malaysia, after the October currency crisis
that threatened to significantly devalue the Ringgit, set strict capital controls limiting the
movement of its currency abroad. This would lead to a dramatic shift in the ability for
local firms to directly invest abroad. This is also noticeable in the statistics presented in
Table 2. With the exception of Thailand, Malaysia experienced the greatest percentage
drop of outbound FDI, having diminished to less than 90% of its original value. To a large
extent, it would also lead to the importance from examining RQ in both its own and host
markets to be of a less er concern in determining outward FDI, relative to the ability to deal
with capital controls imposed on the market when trying to invest abroad.
Table 4 shows results for a second set of regressions where an alternative collection of
control variables is used. L, ST, interest rates, and economic growth are now included for
the host country. L and ST provide measures of how well the financial markets are
performing in the host country, while interest rates and economic growth measure the

general investment climate within each country. Only host country factors are now
examined, primarily to limit the number of independent variables within the model.
It is very interesting to note that as with Table 3, the most consistent variable for being
significant is that of RQ. RQ is significant, to at least the 5% critical level, in all countries
with the exception of Malaysia. As with Table 3, the results for Malaysia not being
significant may be primarily due to the capital control restrictions imposed on the market.
The overall results, particularly for the significance of RQ in determining outbound FDI,
therefore compliment the figures in Table 3, showing the benefit from examining RQ as a
determinant of outward FDI. In particular, the results indicate that multinational
enterprises do place a significant emphasis on the quality, effectiveness, and enforcement of
the host county’s trade and investment regulations when determining where to directly
invest. RQ, as a factor in influencing FDI is at least as important as the macroeconomic
environment of a host country. These results are consistent with the findings of Buckley
and Casson (1985) and Nunnenkamp (2004).
Of the remaining variables tabulated in Table 4 , only short-term interest rates and
economic growth are significant for more than one country. Economic growth, in fact,
seems to be a very effective parameter, being significant to at least the 10% critical level in
all the regressions, with the exception of the Philippines. Interest rates as a determinant of
outbound FDI is significant in three of the countries, all showing a positive relationship.
This is a bit surprising, as one would expect a higher interest rate environment to
discourage investment. However, it may be that during the period under investigation, the
high interest environment most countries were operating in led to an advantage for host
firms to capitalize in the market if they could borrow in their home market at rates lower
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than in the host country. High borrowing rates for local firms may have led to a distinct
advantage for foreign firms that did not require borrowing money in the market. This view
can be supported with the work of Desai, Foley, and Hines Jr. (2004) who found that in
the case of American affiliates, the decision to borrow capital from the home or host
nation is a response to local inflation and political risks, and is more costly in countries

with underdeveloped capital markets and those providing weak legal protections for
creditors.
Finally, and as a supplement to the above analysis, Tables 6 and 7 re-examine the
models in the context of only measuring intra-ASEAN outward FDI within the five
countries of analysis. Instead of examining the level of outward FDI from the home to host
country, the dependent variable is now measured as the proportion of outward FDI to a
host country over the total outward FDI from the home country to all other countries in
the sample. Doing so will account for the fact that in recent years, a large outflow of capital
has occurred from ASEAN nation states to other growth areas, in particular China.
China’s ability to attract FDI has allegedly made it more difficult for other emerging
markets to attract FDI. The then Prime Minister of Malaysia, Mahathir Mohammad,
explained his country’s fall in foreign direct investment from RM 19 billion in 2001 to RM
2 billion in the first half of 2002 by stating: ‘‘Everyone is feeling the pinch because the
amount of FDIs has shrunk and then, a lot of that is going to China’’ (cited in McKibbin
& Woo, 2003).
While the number of FDI source countries in China is quite large, only a handful of
countries account for the sums invested. Hong Kong is the largest single investor and the
newly industrialized economies (NIEs) have been the largest investors as a group. Four
ASEAN countries (Indonesia, Malaysia, Philippines, an d Thailand) have substantially
increased their presence in China since the early 1990s. Also, the overseas Chinese network
in Singapore has made her the largest investor in China from the ASEAN region,
accounting for more than twice the combined investment of the other four ASEAN
countries up to 1998 (see Table 5). Since, 1998, this has been further pronounced ( Wong &
Chan, 2002). Nevertheless, although China has dominated FDI inflows in Asia, the growth
has not necessarily been at the expense of ASEAN. Some co mmentators suggest other
reasons for the lack of FDI flows to ASEAN nations in recent times. Wu, Siaw, Sia, and
Keong (2002), for example, state that FDI flows to the five ASEAN nations plunged as a
result of the Asian financial crisis in 1997–1998, and have remained subdued due to an
unfavorable investment climate.
The results from the panel regressions in Tables 6 and 7 which use proportional data,

however, do re-affirm the previous results in Tables 3 and 4. When outward FDI is
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Table 5
Accumulated FDI stock in China by ASEAN-5 countries (US$ million, %)
Source area 1983–1990 1991–1995 1996–1998 1983–1998
Amount Share Amount Share Amount Share Amount Share
ASEAN-4 110 0.45 2207 1.87 2418 1.92 4735 1.76
Singapore 266 1.08 3788 3.21 7819 6.20 11873 4.42
Note: The ASEAN-4 countries include Thailand, Philippines, Malaysia and Indonesia.
Source: FDI statistics, MOFTEC.
H.G. Rammal, R. Zurbruegg / International Business Review 15 (2006) 401–414410
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Table 6
Determining proportional outward FDI
Indonesia Malaysia Philippines Singapore Thailand
Host country 0.1025 À 1.7757 À0.0790 0.6455 0.2962
Economic activity (0.4530) (1.2326) (0.1007) (0.4696) (0.2801)
Host country inflation 0.0050 À0.0135 À0.0019 À0.0056 À 0.0039
a
Rate (0.0226) (0.0105) (0.0014) (0.0039) (0.0019)
Host country 0.3646
a
0.0711 0.2081 0.7579
a
0.8954
b
Regulation quality (0.1480) (0.4019) (0.17001) (0.3624) (0.2284)
Home country À0.0634 2.4563 0.4209
c
1.8909

c
0.0975
Economic activity (0.4203) (1.5414) (0.2325) (1.0310) (0.1501)
Home country À0.0001 0.1482 0.0327 À0.0308 0.0057
Inflation rate (0.003) (0.1366) (0.0314) (0.0417) (0.0188)
Home country 0.0596 0.2849 À0.3929 À0.1407 0.0977
Regulation quality (0.1327) (1.1576) (0.7406) (0.0996) (0.3278)
F-statistic 4.0986
b
0.7239 3.0334
a
3.3863
a
3.9624
a
Adjusted R
2
0.6070 0.3175 0.4809 0.4829 0.5593
All coefficient estimates are from a fixed-effects panel regression of outward FDI from the specified country to the
remaining four countries in the sample. The dependent variable is measured as the proportion of outward FDI to
a host country over the total outward FDI from the home country to all other countries in the sample. Each
regression is run from a balanced panel dataset consisting of 24 observations over four cross-sections (countries).
Economic activity is measured as the logarithm of GDP in $US. Weighted cross-sections are utilized and figures in
brackets are White heteroscedastic-corrected standard errors.
a
Represents significance at the 5% critical level.
b
Represents significance at the 1% critical level.
c
Represents significance at the 10% critical level.

Table 7
Alternative results for determining proportional outward FDI
Indonesia Malaysia Philippines Singapore Thailand
Host country 0.098 0.4069 À2.476 0.9575 0.7376
Liabilities (0.1300) (0.6700) (2.2512) (0.6241) (1.2393)
Host country stock turnover 0.0901 À0.6944 À0.6548 0.6826
a
À0.3209
(0.0593) (0.7268) (0.7726) (0.2097) (0.1992)
Host country 0.4438
a
0.0412 1.4530
a
0.4491
b
1.1107
a
Regulation quality (0.0615) (0.1079) (0.4357) (0.2180) (0.1506)
Host country interest 0.0096 0.0183
a
0.0041 À0.0034 À0.0057
Rate (0.0084) (0.0056) (0.0097) (0.0076) (0.0050)
Host country 0.0080
b
0.0325
b
0.0063 À0.0128 0.0168
c
Economic growth (0.0039) (0.0133) (0.0166) (0.0097) (0.0087)
F-statistic 9.6747

a
2.364
c
0.2837 6.7955
a
6.5978
a
Adjusted R
2
0.7592 0.4349 0.3189 0.6684 0.6807
All coefficient estimates are from a fixed-effects panel regression of outward FDI from the specified country to the
remaining four countries in the sample. The dependent variable is measured as the proportion of outward FDI to
a host country over the total outward FDI from the home country to all other countries in the sample. Each
regression is run from a balanced panel dataset consisting of 24 observations over four cross-sections (countries).
Economic activity is measured as the logarithm of GDP in $US. Weighted cross-sections are utilized and figures in
brackets are White heteroscedastic-corrected standard errors.
a
Represents significance at the 1% critical level.
b
Represents significance at the 5% critical level.
c
Represents significance at the 10% critical level.
H.G. Rammal, R. Zurbruegg / International Business Review 15 (2006) 401–414 411
measured as a proportion of only intra-ASEAN FDI, RQ still is prevalently significant for
the majority of the regressions, and is definitely the most common significant parameter
when compared to the control variables. As what would be expected, after regulation
quality, economic activity and economic growth tend also to be significant factors. The
control variables are not, however, as significant as with the original regressions in Tables 3
and 4. In some cases, such as in Table 6 for Malaysia, none of the parameters are
significant and the model as a whole fails to be significant. In this particular case, and as

previously mentioned, the failure of the model may have more to do with the restrictive
capital constraints imposed on foreign investment since the 1997 Asian crisis. Overall, the
results from both Tables 6 and 7 are, however, in alignment with the original results. This
further supports the fact that even if FDI is only measured within and between the
ASEAN countries, regula tion quality is a significant determ ining factor for outward FDI
within ASEAN.
5. Conclusion
This paper explores what impact regulatory factors can have on outward FDI from
ASEAN countries to fellow member states once various economic conditions are taken
into account. The results indicate that there is a relatively strong, positive relationship
between the quality and effectiveness of trade and investment regulations employed within
the host country, and the amount of FDI received by the hos t country.
Extant literature on MNC strategy states that the decision to invest in a host market is
influenced by the presence of strong economic fundamentals, such as in the host economies
(see Dunning, 2000). Kokko and Gustavsson (2004) state that the most important of these
economic fundamentals are market size and the level of real income, with skill levels in the
host economy, the availab ility of infrastructure and other resources that facilitate efficient
specialization of production, trade polici es, and political and macroeconomic stability as
other central determinants. However, the emergence of regional trading blocs has resulted
in deep integration where many of these determinants do not distinguish effectively among
the nations within a region (Kokko & Gustavsson, 2004). What are then the cross-country
differences that explain the variation in the amount of FDI flow between the ASEAN
nations?
The findings of this paper reveal that within the ASEAN region, the MNCs decision to
invest in a nation is influenced by the quality of the regulations in the host economy.
Regulations that are aimed at encouraging market-openness provide host nations a
competitive advantage that is used to encourage inward FDI. Some researchers believe
that openness to the global economy is a necessary condition for sustained growth.
According to Kobrin (2004), developing nations have increasingly recognized that FDI
provides a stable form of capital investment, and are therefore attempting to follow the

developed nations in attracting flows of FDI through both liberalizing regulations and
providing incentives to investors.
RQ and effectiveness has become more relevant to the ASEAN host nations in the
aftermath of the Asian financial crisis. Thompson and Poon (2000) found that foreign
MNCs had anticipated, and hoped that the Asian crisis would help to bring about
governmental and institutional reforms throughout ASEAN countries, making the region
more attractive and stable for FDI. The findings of this study suggests that if regulatory
reforms aimed at encouraging inward FDI are not instituted and fully implemented by
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regional governments, the ASEAN region may well prove to be a less attractive place for
MNCs.
Moreover, the importance of a regulatory framework that encourages trade seems to be
a more dominant factor in explaining intra-ASEAN trade than some more commonly
examined macroeconomic conditions. This paper presents mixed evidence of the
importance of various economic factors. Although economic growth, as expected, shows
to be a significant determinant, the importance of other macroe conomic variables is not
consistently significant across the five countries examined. Although this may be in part
due to the limitations prevalent from using a small sample set, it is also likely due to the
fact that the various East Asian nations reacted very differently to the 1997 Asian crisis,
potentially leading to the infor mation content contained in examining various economic
variables not necessarily being homogenous in nature. This would also suggest that future
research should also take care to treat analyses of FDI flows on a country-by-country
basis, rather than assuming that the factors influencing one market are likely to be the
same in other countries.
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