Kwok2000 - Teoria downstream Upstream

Internationalizationand Firm Risk: An
Upstreamr-DownstreamHypothesis
ChuckC. Y. Kwok*
UNIVERSITY OF SOUTH CAROLINA
DavidM. Reeb**
AMERICAN UNIVERSITY
Corporateinternational diversifica-
tion theory posits that multina-
tional corporations (MNCs)should
have lowerriskand higherfinancial
leverage than purely domestic cor-
porations (DCs). We suggest an al-
ternative upstream-downstreamhy-
pothesis according to which the
overall effect of internationaliza-
tion on the risk and leverage of
MNCs is expected to vary with
home and targetmarketconditions.
The empirical results are consistent
with the suggested hypothesis.
M uch of the early literature on the
multinational corporation (MNC)
posits a diversification benefit for MNCs,
leading to lower levels of risk and to
subsequently higher levels of debt. Ini-
tial research by scholars such as Hughes,
Logue, and Sweeny (1975) finds evi-
dence consistent with the diversification
benefit. However, more recent research
by Bartov, Bodnar and Kaul (1996) and
Reeb, Kwok and Baek (1998) finds that
firm risk is positively related to inter-
nationalization. Similarly, research on
leverage finds that US MNCs have sig-
nificantly lower levels of debt in their
capital structure relative to domestic cor-
porations (DCs) (e.g. Lee and Kwok,
1988). An implication of this body of
research is that firm risk is increasing in
corporate internationalization.
Owing to data availability, the re-
search on the financial aspects of firm
internationalization has focused primar-
ily on US based firms. We explore how
internationalization affects risk and le-
verage for firms based in emerging mar-
kets and in other developed markets.1
Specifically, we argue that when firms
from more stable economies make inter-
national investments, it tends to increase
their risk and leads to a reduction in debt
usage. By contrast, when firms from less
*Chuck Kwok is Professor of International Business at the University of South Carolina. He
was Vice President-Administration of the Academy of International Business in 1995-96.
* *David Reeb is an Assistant Professor in the Kogod School of Business at American University.
His research focuses on the financial aspects of international business.
We would like to thank Andy Chui, three anonymous reviewers, and the participants at the
Academy of International Business 1998 Annual Conference in Vienna Austria for their valu-
able input. Chuck Kwok gratefully acknowledges the support of the Center for International
Business Education and Research (CIBER)at the University of South Carolina.
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INTERNATIONALIZATIONAND FIRMRISK
stable economies make international in-
vestments, it decreases their risk and al-
lows for greater debt utilization. In other
words, we predict that the relative busi-
ness risk among countries influences the
risk impacts of foreign direct invest-
ments. Thus, as firms invest economi-
cally upstream they decrease their risk,
while downstream investments lead to
greater firm risk.
Our focus is not on whether firm finan-
cial characteristics differ across coun-
tries. Instead, our emphasis is on how
internationalization may affect these
characteristics differently in different
countries. Underlying our analysis is the
contention that differences in financial
characteristics between US MNCs and
DCs may not be representative of the dif-
ferences between MNCs and DCs in a
global context. To test our hypothesis
that the risk impacts of firm internation-
alization are a function of the relative
risks in the home and target country, we
use firm data from 32 different countries
to examine the relationship between le-
verage and internationalization. We also
use the multi-country data set to explore
the relationship between risk (both total
and systematic) and internationaliza-
tion.
LITERATURE REVIEW
During the 1970s, researchers such as
Hughes et al. (1975) and Rugman (1976)
hypothesize that MNCs provide a diver-
sification benefit to shareholders because
they possess cash flows in imperfectly
correlated markets. Yet, evidence in Bar-
tov et al. (1996) suggests an increase in
systematic risk with internationalization
due to greater exchange rate risk. Simi-
larly, Reeb et al. (1998) posit that MNCs
may have increased risk from a variety of
risk factors (such as exchange rate risk,
political risk, agency issues, asymmetric
information, etc.) that offset the diversi-
fication benefit from imperfectly corre-
lated returns. Using a portfolio approach
in an empirical analysis of 880 US based
MNCs, they report that systematic risk is
positively related to internationaliza-
tion.
Focusing on leverage, Agmon and Les-
sard (1977) and Fatemi (1984) posit that
the MNC diversification benefit reduces
the present value of bankruptcy costs
and allows increased debt usage in mul-
tinationals. However, other researchers
have noted that internationalization may
lead to higher debtholder monitoring
costs and, therefore, lower levels of le-
verage in the MNC (Burgman, 1996).
Consistent with greater agency costs, Lee
and Kwok (1988), Burgman (1996), and
Chen et al. (1997) report significantly
higher debt ratios in DCs relative to
MNCs.
We seek to extend this literature by
focusing on an aspect of risk that is often
neglected in this research. Specifically,
we focus on the relative business or en-
vironmental risk that a firm faces with
foreign direct investments. We suggest
that owing to differences in the relative
business risks of foreign operations,
MNCs from other parts of the world will
be observed to respond differently to FDI
than US multinationals. Specifically, we
suggest in the next section that risk is
increasing in FDI for US firms, but de-
creasing in FDI for firms headquartered
in emerging markets.
THE UPSTREAM-DOWNSTREAM
HYPOTHESIS
International business theory suggests
that foreign direct investment (FDI) is
motivated by the desire to exploit firm-
specific assets such as technological ad-
vantages, management skills, and geo-
graphical advantages (Hymer (1976) and
612 JOURNAL OF INTERNATIONAL BUSINESS STUDIES

CHUCKC.Y.KWOK,DAVIDM. REEB
Dunning (1977)). However, the agency
costs arguments of Lee & Kwok (1988)
and Burgman (1996) focus on the risks
and costs associated with firm interna-
tionalization. They suggest that MNCs
have higher agency costs of debt (due to
higher monitoring costs, higher auditing
costs, languagedifferences,varyinglegal
systems, capital market imperfections,
and differentasset structures)and imply
that MNCs should have lower levels of
debt in their capital structures.
It is posited in this analysis that al-
though these cross-border consider-
ations play a significantrole, the relative
business risk of a foreign market may
also lead to changes in firmcapital struc-
ture and risk.2 These effects are not de-
pendent upon different currencies or le-
gal systems but may simply stem from
the differentbusiness risks of operations
in those regions. Much as Modigliani
and Miller (1958) suggest the existence
of risk classes among firms, we suggest
that there are risk classes among coun-
tries.
Internationalization and
Total Risk
We begin the analysis on total risk by
focusing on the risk differences among
projectsin differentcountries.Forexam-
ple, a projectundertakenin an emerging
market is in a more volatile operating
environment than a project in a larger
developed economy. Emerging market
projects have potentially greater infra-
structure risks, customer risks, banking
system/payment risks, labor risks, and
political risks. Infrastructurerisk, for ex-
ample, includes such items as the in-
creasedrisk of transportationdelays due
to fewer roads, highways, railways, less
developed air routes and greater sus-
ceptibility to route closings due to less
reliable machinery operating on these
routes. Additionally, infrastructurerisks
include a greaterrisk of telephone and
power outages and delays in mail deliv-
ery. Alternatively, greaterlaborrisk may
stem from differences in health care, ed-
ucation, and living conditions for em-
ployees, which can lead to greatervola-
tility in work force performanceand at-
tendance.
Although the evidence indicates the
net benefit of FDIoutweighs the risk just
noted (since FDI leads to a net increase
in shareholder wealth), these risks nev-
ertheless exist (Errunza and Senbet
(1984) and Morck and Yeung (1992)).
This suggests thatwhen a firmheadquar-
tered in a more stable, developed econ-
omy expands its direct investments into
a less stable market (i.e. going down-
stream),the overall firmrisk is likely to
increase. Conversely, when a firmhead-
quarteredin an emerging market econ-
omy expands its investments in a devel-
oped economy (i.e. going upstream),the
firm's total risk is likely to decrease. In
essence, we suggest that FDI risk is in-
creasing or decreasing in firm interna-
tional activity based on the relative risk
profiles of the home and targetcountries.
Systematic Risk
Relatingto the literatureof MNCs'sys-
tematic risk following Bartov et al.
(1996) and Reeb et al. (1998), our argu-
ment can be extended to the systematic
risk area. The MNC, by definition, has
operations in various countries. The sys-
tematic risk of an ith operation, bi is de-
fined as:
bi= (pimUi)l/m, (1)
where Pim is the correlation coefficient
between firm i's return and the market
VOL. 31, No. 4, FOURTHQUARTER,2000 613

INTERNATIONALIZATIONAND FIRM RISK
return, o-iis the standard deviation of the
return of firm i, and 0-m is the standard
deviation of the market return.
An operation's beta is influenced by
the operation's business nature as well
as the economic system in which the
operation is located. For a project lo-
cated in a more volatile emerging econ-
omy, the total risk, oi, tends to be higher.
Unless the higher standard deviation is
offset by a lower correlation coefficient
Pim, the systematic risk, bi, tends to be
higher.2 Conversely, for a project located
in a more stable economy, o-itends to be
lower. Unless its correlation coefficient
with the market return is substantially
higher, the project beta tends to be lower.
The overall systematic risk of a multi-
national corporation (bMNC) is simply
the weighted average of the betas of its
business operations located in different
countries:
N
bMNC= Ewibi (2)
i=1
where wi is the fraction of MNC's total
capital invested in the ith country's op-
eration. As a firm headquartered in a
more stable economy expands its direct
investments into a less stable market, the
overall beta of the firm may increase
since the beta of the new operation in the
emerging market may be higher due to
potentially greater environmental risk.
In contrast, when a firm moves from an
emerging market economy to a devel-
oped economy, the overall beta of the
firm may decrease.'
The ability to arbitrage markets could
also differ based upon home/target coun-
try economic differences. For example,
the ability to shift income among differ-
ent tax regimes could be related to the
host/target government degree of sophis-
tication. Firms based in countries with
developed economies and with govern-
ments that possess greater resources may
have fewer opportunities to shift in-
come than firms based in emerging mar-
kets (Plasschaert, 1985). Likewise, firms
based in developing economies may
have different opportunities to arbitrage
labor and capital markets relative to
firms based in emerging market. Firms
moving upstream have the opportunity
to hire employees with different skill
sets and experiences than in their home
country, while firms based in developed
economies are typically portrayed as
gaining access to lower cost inputs. What
is important is that the opportunities to
arbitrage international markets with firm
internationalization differ between firms
based in less developed economies than
firms based in more developed econo-
mies. An implication is that firm behav-
ior towards international activity differs
depending upon whether a firm is mov-
ing upstream or downstream.
We suggest that for MNCs from the
United States where the economy is
among the most stable in the world,
overseas expansion tends to increase
risk, and such an increase may not be
totally offset by the risk reduction due
to international diversification. The net
increase in corporate risk may there-
fore lead to a downward adjustment of
leverage. Conversely, for corporations
in emerging markets, international in-
vestments into developed economies
lead to the reduction of firm risk; their
leverage may therefore be adjusted up-
wards. We label this our upstream-
downstream hypothesis.5 The risk as-
pect of the upstream-downstream hy-
pothesis can be stated formally and in
the alternative as:

Hi: The degree of firm international-
ization is positively (negatively) asso-
ciated with firm risk for firms based in
more developed (less developed)
economies which make investments in
less (more) developed markets.
Leverage
As alluded to above, the association
between risk and firm internationaliza-
tion suggests a leverage effect as well. As
firm risk increases (decreases), tradi-
tional capital structure theory suggests a
decrease (increase) in debt utilization.
The state of capital market development
could also impact the availability of ex-
ternal financing in some markets. When
firms in less developed markets expand
internationally, they may gain access to
debt that was not available previously,
while the opposite is the case with firms
from the US.6 Therefore, multinational
firms from emerging markets with weak
banks and undeveloped debt markets are
more likely to increase their debt when
they gain access to more debt than mul-
tinationals from more developed mar-
kets whose domestic firms already have
access to debt. This leads to our second
formal hypothesis, which allows us to
examine the leverage aspect of the up-
stream-downstreamhypothesis:
H2: The degree of firm international-
ization is negatively (positively) asso-
ciated with leverage for firms based in
more developed (less developed)
economies, which make investments
in less (more) developed markets.
While we do not neglect the signifi-
cance of cross-border diversification
benefits, our upstream-downstream hy-
pothesis predicts that the overall effect
of internationalization on the leverage of
MNCs may vary, depending on home
and target market conditions. Using a
sample of 1,921 firms from 32 countries,
this research empirically examines these
predictions.7
DATA DESCRIPTION
Research into the financial character-
istics of MNCs requires choosing an ap-
propriate proxy for internationalization
(the degree of international involve-
ment). The most common variable cho-
sen is the foreign sales ratio because the
data is widely available. However, Lee
and Kwok (1988) and Burgman (1996)
note that this approach potentially mixes
export sales with foreign subsidiary
sales. Following Reeb et al. (1998), this
analysis uses the foreign asset ratio
(FAR) to measure internationalization.8
This is computed as foreign assets di-
vided by total assets. This may be a bet-
ter measure of foreign subsidiary in-
volvement (i.e. international investment)
and alleviates the problem of mixing in-
ternational trade and investment.
Firm leverage (LEVER)or the debt ra-
tio is measured as long term debt (LTD)
divided by the sum of long term debt and
the market value of equity (MVE). This is
consistent with the measures employed
in Lee and Kwok (1988), Burgman
(1996), and Chen et al. (1997).9 Total risk
(TOTRISK)is defined or measured as the
standard deviation of monthly returns
using 60 months of return data.10
Data Sources
The primary data source in this anal-
ysis is the Disclosure WorldScope Data-
base. This database contains information
on approximately 17,000 public firms
from around the world. The WorldScope
Database contains standardized data that
is compiled (by taking into account
the various accounting conventions
employed in different parts of the

world ) with the stated purpose of facil-
itating "comparisons between compa-
nies within and across national bound-
aries".11Companies with complete data
from 1992 to 1996 were initially se-
lected. The time period was based upon
data availability as information for
non-US firms is limited. Owing to con-
cerns with size factors,the analysis was
restricted to firms with assets greater
than US$100 million. Firmsin regulated
industries (utilities, financial, and trans-
portation)were also excluded. Applying
these filters leaves 1,921 firms from 32
countries. Although ourtests use the for-
eign asset ratio as a continuous variable,
a simple rule of FAR > 1% would clas-
sify 914 of the firms as domestic corpo-
rations (DCs)and 1,007 as MNCs.
Table 1, Panel A lists the 32 countries
from which the sample is drawn. Panel
A also shows the number of companies
in the sample fromeach country. Owing
to our stringentrequirementof complete
data,many of the small emergingmarket
firms are excluded from the analysis.
This has the effect of reducing our sam-
ple size, but also minimizes non-syn-
chronous trading and firm size con-
cerns.12 These issues are addressed in
greaterdetail in later sections.
Panel B in Table 1 gives the fifteen-
industry category scheme used in this
analysis along with the number of firms
in each industry. Following Harris and
Raviv (1991), industries were classified
as having high, medium, orlow levels of
debt. These areused as industry control
variables.
Descriptive statistics are provided in
Table 2 for the 1,921 firms included in
the sample. Panel A shows the means,
standarddeviations, andmedians forthe
foreign asset ratio, the return on assets,
leverage, intangibles, market-to-bookra-
tio, non-debt tax shields, volatility, and
TABLE1
SAMPLEDISmIBurION
PANELA: COUNTRYLIST
This panel shows the number of compa-
nies from each couintryin the complete
dataset and in the datasubsample.A sub-
sample is used which includes oinlyfirms
with 36 months of complete return data
within the period of 1994-96.
Full Data
Country Sample Subsample
Argentina* 1
Australia 59 48
Austria 2 1
Belgium 1 1
Canada 101 86
Denmark 2 1
Finland 3 1
France 28 18
Germany 17 5
Greece 1 1
Hong Kong* 11 8
India* 1
Ireland 10 7
Italy 5
Japani 537 297
Malaysia* 22 13
Mexico* 7 3
Netherlands 7 5
New Zealand 7 6
Norway 3 1
Singapore* 23 16
South Africa* 25 20
South Korea* 42 11
Spain 5 4
Sweden 2
Switzerland 11 6
Taiwan* 1
Thailand* 5 3
Turkey* 6 5
United Kingdom 204 165
United States 771 587
Venezuela* 1 1
Total Numberof
Companies 1921 1320
* Denotes countries classified as emerging
markets.

CHUCKC.Y. KWOK,DAVIDM. REEB
TABLE1 (CONT.)
PANELB: INDUSTRYCLASSIFICATION
This panel shows the industry classifica-
tion of the firmsin the sample. Following
Harrisand Raviv (1991), industries were
classified into categories with Low (L),
Mediuim(M),or High (H)debt.
Industry
# of by Debt
Industry Companies Level
Appareland
Retailers 206 M
Automotive 60 M
Chemicals 141 M
Conistruction 168 M
Diversified 108 H
Drugsand
Cosmetics 68 L
Electricaland
Aerospace 51 L
Electronics 152 L
Food, Textiles, and
Tobacco 166 M
Machineryand
Equipment 100 L
MetalProducers 172 L
Miscellaneous 243 M
Oil, Gas,and Coal 103 L
Paper,Printing,
and Pub 101 M
Recreation 82 M
the natural log of assets for the sample.
The mean FAR value is 15.35% while
the median is only 4.65%. Given the
MNC/DC composition of the sample, this
is not surprising. The mean and median
ROA values of 5.52% and 4.65% are
much closer to each other. However, the
leverage values differ substantially be-
tween the mean (17.54%) and the me-
dian (7.43%), which is due to the large
number of firms with zero debt in their
capital structure. The mean and median
values for the intangibles, market-to-
book ratio, and non-debt tax shields also
differ substantially. These deviations
suggest that a search for outliers may be
appropriate.13 Market-to-book ratio is
defined as the market value of equity
divided by the book value of equity.
Non-debt tax shields include deprecia-
tion and investment tax credits, which
reduce the need for debt to minimize
taxes. This variable is measured in tens
of millions. Panel B in Table 2 gives the
same descriptive statistics for various
subsets of the sample.
Owing to the problems associated with
panel data, this study uses a pooled re-
gression in the multivariate analysis.14
Thus, the five years of data for each firm
is averaged and the primary regressions
have 1,921 observations. A five-year av-
erage may also be a more appropriate
measure of the firm's target capital struc-
ture.
EMPIRICALFINDINGS
Total Risk and
Internationalization
We explore the relationship between
total risk and firm internationalization
using the pooled 1,921 firm sample. To-
tal risk (TOTRISK) is defined or mea-
sured as the standard deviation of
monthly returns using 60 months of re-
turn data.15 As total risk may be affected
by such items as firm size, asset type,
leverage, and growth options, these are
included as control variables. The fol-
lowing specification is then tested:
TOTRISKi = Bo + Bj(FARi)
+ B2(LTA1) + B3(INTANGi)
+ B4(LEVER1)+ B5(MTB) (3)
where TOTRISK is the total risk of firm i
described above, FAR is the internation-
alization proxy, LTA is the natural log of
total assets, INTANG is the firm's R &D,

INTERNATIONALIZATIONAND FIRmRISK
TABLE2
SUMMARYSTATISTICS
PANELA: DESCRfPIVEINFORMATION
The datais comprisedof 1921firmswith assetsgreaterthan$100 million forthe period 1992
to 1996. Informationregardingmean and median leverage, foreignasset ratio, log of asset
size, non-debt tax shields (in 10,000,000s), price to book ratio,EBITvolatility, and profit-
ability is provided.
Variable Mean Std Deviation Median
ForeignAsset Ratio 15.34% 20.42 4.65%
Returnon Assets 5.52% 5.14 4.65%
Leverage 17.54% 23.19 7.43%
Intangibles 1.55 3.75 0
Market-to-BookRatio 2.80 6.62 1.99
Non-DebtShields 4.11 11.04 1.92
Logof Assets 14.05 1.36 13.93
PANELB: SUBSAMPLEDESCRIPTIVEINFORMATION
This panel gives summaryinformationregardingvarioussubsamplesof the dataused in this
study.Subsampleinformationis providedforUS firms,Japanesefirns, EmergingMarketfirms.
Variable Mean Std Deviation Median
US Firms
ForeignAsset Ratio 16.77% 19.35 10.48%
Leverage 17.68% 18.28 12.78%
Logof Assets 14.06 1.36 13.92
Japanese Firms
ForeignAsset Ratio' 5.61% 11.03 0
Leverage 16.0% 30.79 2.86%
Non-DebtShields 9.01 22.32 .51
Logof Assets 14.15 1.43 14.17
EmergingMarket Firms
ForeignAsset Ratio 10.16% 22.79 0
Leverage 21.99% 25.47 13.08%
Logof Assets 13.72 1.15 13.72
Among the Japanesefirms29.8%of the firmshave positive foreignassets, while in the US
56.6% of the firmshave internationaloperations. This accounts for the differences in the
foreignasset ratiobetween the two subsets. Repeatingour multivariateanalysis using only
those firmswith foreignassets provides similar results to those reported.
618 JOURNALOFINTERNATIONALBUSINESS STUDIES

CHUCKC.Y. KWOK, DAVID M. REEB
LEVERis the leverageproxy, and MTBis
the market-to-bookratio and is a proxy
for growth opportunities. Firm size
(LTA)is included to control for firm de-
fault risk as largerfirms are more stable
and less aptto default (Harrisand Raviv,
1991). Research and development (IN-
TANG)is included to control forthe tan-
gibility of assets because real assets are
easier to sell in the case of default. The
leverage(LEVER)is included as a control
since higher leverage tends to lead to
higher risk. The market-to-bookratio is
included to control for firm growth op-
portunities as firms with higher growth
tend to have higher risk. A positive and
significant coefficient estimate for B1
would be consistent with an increase in
total risk with internationalization.Firm
size is expected to be negatively corre-
lated with total risk. The asset type, le-
verage,and growth opportunities areex-
pected to have a positive correlation
with total risk.
Equation (3) coefficient estimates us-
ing the 1,921 pooled sample are reported
in Table 3 Column 1. The B1 coefficient
estimate is negative but is not signifi-
cantly different from zero. This differs
from recent research that reports an in-
crease in risk with internationalization
for US based MNCs. The estimated coef-
ficients for the control variables for size
(LTA) and asset type (INTANG) are pos-
itive and significant at the 1% signifi-
cance level. The estimated coefficients
for the control variable for growth op-
tions (MTB) and leverage (LEVER) are
not significant at typical significance
levels.
The next step in this analysis is to
estimate Equation (3) using various sub-
sets of the sample. First, we exclude the
US firms and use only the 1150 non-US
TABLE3
REGRESSIONANALYSIS FORTOTALRISK CHANGESWITH
INTERNATIONALIZATION
Excluding Japanese Emerging
Variable All Firms US US Firms Firms Market
CONSTANT 2.08 3.31 -1.48 3.89 .46
(1.16) (1.24) (-.63) (.71) (.03)
FAR -.01 -.03* .05* .02 -.11***
(-.74) (-3.12) (3.92) (.27) (-1.80)
LEVER .54 -.24 3.66* .34 -4.39
(.77) (-.28) (2.79) (.27) (-1.03)
INTANG .16* .22** .16* .18 -1.82
(3.77) (1.98) (3.75) (1.01) (-.82)
LTA .45* .42** .55* .45 .53
(3.50) (2.20) (3.35) (1.18) (.49)
MTB .07 .03 -.02 2.24 .91
(.03) (.83) (-.62) (.63) (1.16)
AdjulSted R2 .02 .02 .07 .00 .03
F-Value 5.58* 3.53* 10.33* .88 1.43
*, **, *** Significant at the 1%, 5%, and 10% level. EGLS Consistent t-values are given in
parenthesis below each coefficient estimate.
VOL. 31, No. 4, FOURTH QUARTER, 2000 619

firms. The results from this regression
are reported in Column 2 in Table 3. The
B1 coefficient estimate is negative and
significantly different from zero at the
1% significance level, which is consis-
tent with the idea that internationaliza-
tion leads to lower levels of risk in the
MNC for non-US based firms.16
In the next regression, the analysis is
repeated using only the 771 US firms and
the results are reported in Column 3 in
Table 3. Consistent with Reeb et al.
(1998) and Bartov et al. (1996), we find
that the B1 coefficient estimate is posi-
tive and significantly different from zero
at the 1% significance level. This implies
that the results in the previous two re-
gressions are due to differences in behav-
ior towards foreign direct investment be-
tween US and non-US firms.
The next largest firm grouping in the
risk subset is from Japan. Equation (3) is
estimated for the Japanese firms and re-
sults are reported in Column 4 in Table
3. The B1 coefficient estimate is not sig-
nificantly different from zero for the Jap-
anese firms. The final regression, re-
ported in Column 5 in Table 3, gives the
results of the regression analysis using
only emerging market firms. The coeffi-
cient estimate for B1 is negative and sig-
nificantly different from zero at the 10%
significance level.17 For Japan, the re-
gression results could be explained as
follows: Japanese foreign direct invest-
ment may go upstream to a country such
as the U.S. where the economy is, argu-
ably, more stable than that of Japan. Or,
it may go downstream to more risky
emerging markets (e.g. China and South-
east Asia). Consequently, the effects may
offset each other and result in little
change in the risk of the MNC with in-
ternationalization. The total risk, there-
fore, does not vary much with interna-
tionalization. Overall, our results are
consistent with our upstream-down-
stream hypothesis.
Systematic Risk
Primary Specification. A potential
concern in examining the relationship
between systematic risk and firm inter-
nationalization is the potential for mea-
surement error in measuring beta.18 To
adjust for possible bias resulting from
the measurement error in analyzing in-
dividual betas, we form portfolios con-
sisting of five securities according to the
firm's origin. Thus, emerging market
firms are grouped together in portfolios
as are developed economy firms. Firms
from the US are also put together in
groups of five. Not all the firms in the
original sample have 36 months of com-
plete return data. Only firms with three
years' return data within the period of
1994-96 are used in forming portfolios.
The number of firms from each country
included in the subsample are shown in
Column 2 of Table 1. This provides a
sample of 264 portfolios with 118 port-
folios of US firms, 16 portfolios of emerg-
ing market firms, and 130 other devel-
oped economy firm portfolios.
The beta for each portfolio is calcu-
lated directly using monthly return data
for the period 1994-1996 (36 months of
return data).19 The monthly market re-
turn used is MSCI-World Index.2" The
calculated portfolio beta is then used in
Equation (4).
Bp= kp + Ap1FARP+ Ap2MTBp
+ Ap3LTAp+ Ap4LEVERp+ ep(4)
where Bp is the beta of the portfolio,
FARp is the average degree of interna-
tionalization for portfolio p, and MTBpis
its market-to-book ratio, and LTA and

CHUCKC.Y.KWOK,DAVID M. REEB
LEVER are the portfolio size and lever-
age proxies. The null hypothesis is that
the coefficient, Ap,, will equal zero if
there is no change in systematic risk
with changes in internationalization. A
significant and positive AP1 coefficient
estimate would indicate that internation-
alization increases the systematic risk of
the firm. MTBp is included to control for
growth opportunities; previous research
suggests that this variable may have a
negative relationship with systematic
risk. Size and leverage are also included
as potential control variables and is con-
sistent with the specification in Reeb et
al. (1998).
Equation (4) coefficient estimates us-
ing the subsample of 1,320 firms (264
portfolios) are reported in Column 1 of
Table 4. The AP1 coefficient estimate is
negative but it is not significantly differ-
ent from zero at any standard signifi-
cance level. This is in contrast to the
findings in Reeb et al. (1998) using only
US data. The estimated coefficients for
the control variables for size (LTA) and
leverage (LEVER) are significant at the
1% significance level. The estimated co-
efficient for the control variable of
growth options (MTB) is not significant
at the typical significance levels.
The next step in this analysis is to
estimate Equation (4) using two subsets
of the sample. The first subset excludes
the US firms and includes only the 146
non-US firm subset. The regression re-
sults using this subset of the data are
reported in Column 2 of Table 4. The Ap1
coefficient estimate is negative and sig-
level. The regression is repeated using
only the 118 US firm portfolios and the
results are reported in Column 3 of Table
4. Consistent with recent research we
find that the AP1 coefficient estimate is
positive and significantly different from
zero at the 5% significance level. In con-
trast to the findings of Reeb et al. (1998),
the LTA and LEVERcoefficient estimates
are both significant and the MTB coeffi-
cient estimate is not significant. The re-
sults in this regression provide addi-
tional evidence of the differences be-
tween US and non-US firms in their
experience with internationalization.
This evidence indicates that US firms
have an increase in systematic risk with
internationalization, while non-US firms
generally have a decrease.21
Alternative Specifications. Any analy-
sis based on betas is difficult due to the
measurement error problem. One alter-
native to using a portfolio approach is to
impose a filter on the stock returns to
minimize the potential for measurement
error. This approach consists of setting
all of the returns greater than the 0.995
fractile or less than the .005 fractal equal
to the 0.995 and .005 fractal values and
allows the use individual security re-
turns.22 We repeat the analysis using the
fractal betas and report results in Col-
umn 4 in Table 4. Consistent with the
portfolio evidence, there is no significant
relationship between firm international-
ization and firm beta in the aggregate.
However, for the non-US firms, there is a
negative relationship between firm inter-
nationalization and systematic risk. In
contrast, the US firms have a positive
association between the foreign asset ra-
tio and beta. These results are consistent
with the portfolio regressions and with
the upstream-downstream hypothesis.
Also consistent with our hypothesis is
the insignificant positive relationship
between systematic risk and internation-
alization for Japanese firms. We find a
significant (at the 10% level) and nega-
tive relationship between firm interna-
tionalization and systematic risk in the
emerging market firms.

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Ourfinal alternativespecifications are
motivated by the concern that portfolios
comprised of 5 securities arepotentially
insufficient to mitigate measurement er-
ror. As the portfolio beta is used as the
dependent variable in this analysis, this
is of less concern. However, for robust-
ness, we perform the analysis using 20
securities per portfolio and obtain simi-
lar results as reported in Table 4. The
trade-off in using this approach is that
our groupings are less precise. Another
approach is to include the market-to-
book and size variables in the beta esti-
mation procedure, which can lead to
lower measurement error in beta. This
procedurealso leads to similar results to
those reported in Table 4 and they are
consistent with the upstream-down-
streamhypothesis.
Leverage
Primary Specification. Harris and
Raviv (1991) review the literature and
find that capital structure is affected by
firmsize, industry, non-debt tax shields,
market-to-book ratio, expenditures on
intangibles such as R&D, profitability,
and growth options. To study the effect
of internationalization on firm leverage,
these variables are included as controls.
The following regression equation is es-
timated:
LEVERi = AO+ A1(FARj) + A2(ROAi)
? A3(LTAi)+ A4(INTANGi)
? A5(MTBi) + A6(SHIELDSi)
? A7(INDUST1l) + A8(INDUST2i)
(5)
where the dependent variable(LEVER)is
the leverageproxy described above. The
explanatoryvariablesare:(FAR),the inter-
nationalizationproxy;(ROA)returnon as-
sets, (LTA),the naturallog of total assets;
(INTANG),the firms' R&D;(MTB), the
market-to-bookratio;(SHIELDS),the non-
debttax shields such as depreciation;and
(INDUST1)and (INDUST2),the two in-
dustrydummiesto controlforthe industry
effect.23
A negative and significant coefficient
estimate forA1would be consistent with
a reduction in the debt ratio with inter-
nationalization. A positive and signifi-
cant coefficient estimate forA1would be
consistent with an increase in debt asso-
ciated with internationalization (which
would be contraryto previous research
findings based on US MNCs).
The return on assets is included to
controlforfirmprofitabilityas firmswith
greater profits need (and can support)
greatertax shields. Firmsize is included
to control for firm default risk as larger
firms are less apt to default. Research
and development (INTANG)is included
to control forthe tangibility of assets be-
cause real assets are easier to sell if
default arises. The market-to-bookratio
is included to control for firm growth
opportunities. Previous research sug-
gests that firms with greatergrowth op-
portunities use less debt to gain invest-
ment flexibility. Likewise, non-debt tax
shields areincluded to control for differ-
ing needs with regard to obtaining tax
relief (asan alternativeto the tax deduct-
ibility of interest payments). Industry
control variables are included to control
for industry-wide differences in firm
debt usage.
Using the 1,921 firm sample, the re-
sults of the regressionin Equation(5) are
reportedin Column 1 of Table 5. The A1
coefficient estimate is positive and sig-
nificantly differentfromzero at the 10%
significance level, which indicates that
internationalization leads to higher lev-

TABLE5
REGRESSIONANALYSISFORCAPITALSTRUCrURECHANGESWITH
INTERNATIONALIZATION
Excluding Japanese Emerging
Variable All Firms US Firms US Firms Firms Market
CONSTANT 107.75* 133.99* 78.48* 126.07* 26.12
(21.75) (18.74) (13.18) (12.36) (1.02)
FAR .04*** .12* -.12* .04 .13***
(1.65) (3.73) (-4.09) (.49) (1.65)
ROA - 1.13* - 1.22* - 1.24* - 1.39* - 1.18*
(-11.98) (-8.10) (-12.26) (-3.66) (-3.74)
LTA -5.96* - 7.92* -3.80* -7.88* .35
(-16.95) (-15.50) (-8.79) (-10.80) (.19)
INTANG -.76* -.82** -.62* -.48 1.52
(-5.63) (-2.55) (-5.41) (-=1.23) (.67)
MTB .19* .29** .06 .24** - .91
(2.57) (2.38) (.89) (1.95) (-.58)
SHIELDS .03* .03* 5.55* 7.43* .03*
(7.10) (6.36) (7.38) (18.05) (5.96)
INDUST1 -.73 -2.23 1.28 -2.97 1.63
(-.68) (-1.43) (1.02) (-1.54) (.36)
INDUST2 1.99 -.32 5.46** -6.08 -5.26
(.92) (-.10) (2.11) (-1.13) (-.73)
Adjusted R2 .21 .23 .31 .61 .21
F-Value 63.95* 44.51* 43.61* 106.24* 5.73*
*, **, *** Significantat the 1%, 5%, and 10% level. EGLSConsistentt-values aregiven in
parentiesis below each coefficient estimate.
els of debt in the capital structure. This
evidence is in pointed contrast to the
findings in Lee and Kwok (1988) and
Burgman (1996) using only US data.
Consistent with Titman and Wessels
(1988), the estimated coefficients for
the control variables for profitability
(ROA), size (LTA), intangible assets (IN-
TANG) are negative and significant at the
1% significance level. Consistent with
Kester (1986), the estimated coefficients
of the control variables for growth op-
tions (MTB) and non-debt tax shields are
positive and significant at the 1% level
as well. However, the estimated coeffi-
cients for the industry control variables
(INDUST1 and INDUST2 ) are not signif-
icantly different from zero.
As the aggregate regression may mask
important differences among firms based
in different countries, the next step in
this analysis is to estimate Equation (5)
using various subsets of the sample. In
the first subset regression, we exclude
the US firms and use only the 1150
non-US firms. The results from this re-
gression are reported in Column 2 in Ta-
ble 5. As in the first regression, the A1
coefficient estimate is positive and sig-
nificantly different from zero (at the 1%
significance level in this regression). The
coefficient estimate increases threefold
in size with the exclusion of the US
firms. Given these strong differences
with previous findings on US firms, the
regression is repeated using only the 771

CHUCKC.Y. KWOK, DAVID M. REEB
US firms, and the results are reported in
Column 3 in Table 5. Consistent with
previous research we find that the A1
coefficient estimate is negative and sig-
significance level. This suggests that the
results detected in the first two regres-
sions are not due to methodological dif-
ferences with previous research but, in-
stead, stem from different behavior be-
tween US and non-US firms in response
to internationalization.
The next largest firm grouping in our
sample is from Japan. Equation (5) is es-
timated for the Japanese firms and is re-
ported in Column 4 in Table 5. The A1
coefficient estimate is not significantly
different from zero for the Japanese
firms. Column 5 in Table 5 reports the
results of the regression analysis using
only emerging market firms (i.e. the firm
home country is an emerging market).
The coefficient estimate associated A1 is
positive and significantly different from
zero at the 10% significance level.
Alternative Specifications. One poten-
tial concern is that the proxy for leverage
includes the market value of equity in
the denominator, which could impact
the leverage proxy if changes in the mar-
ket value of equity are correlated with
FAR. Therefore, as a robustness check,
we use total assets to normalize the debt.
We also consider measuring leverage as
total liabilities (i.e. long-term debt plus
current liabilities) scaled by total assets
and as total liabilities scaled by the sum
of total liabilities and the market value of
equity. Our results are also robust to
these alternative specifications.
Another potential concern is our mea-
sure of growth opportunities. Baber,
Janakiraman, and Kang (1996) suggest
using a factor analysis based composite
measure of growth opportunities and in-
dicate that their approach improves the
power of the testing. Regression results
obtained using their exact specification
for the growth measure are consistent
with the results in Table 5. We also ex-
plore the issue of our simultaneous use
of industry and R &D, whose interaction
may mitigate the control for tangibility of
assets. The concern is that the differ-
ences we find could stem from the ability
to put forward collateral security in ob-
taining or issuing debt instruments. Con-
sequently, we repeat the analysis using
only manufacturing firms, as this group
is more homogeneous in terms of its abil-
ity to obtain securitized debt. Once
again, we find that US firms have lower
leverage with increasing firm interna-
tional activity and that non-US firms
have a higher debt usage with greater
firm internationalization.
We also consider the extent of capital
market development since companies
headquartered in countries with poorly
developed equity markets may use more
debt simply due to limited equity avail-
ability. As we are comparing MNCs and
DCs within the same countries, this
should be of less concern. However, for
robustness, we repeat the estimation of
Equation (5) and include the ratio of the
market value of all public equity to the
gross domestic product. Although inclu-
sion of this variable slightly increases
the explanatory power of the model, the
coefficient estimate is insignificant at
standard levels and the results are simi-
lar to those reported in Table 5.
Finally, we consider using an alterna-
tive measure of home country risk. Spe-
cifically, we measure home country risk
using the previous 10 years of domestic
stock market volatility. Sorting by mar-
ket volatility (the coefficient of variation)
and repeating the analysis, we find that
for firms headquartered in the high vol-
atility markets there is a positive rela-

tionship between firm international ac-
tivity and leverage. In contrast, for firms
headquartered in the lower volatility
markets there is a negative relationship
between international activity and lever-
age. These findings are consistent with
our upstream-downstream hypothesis.
SUMMARY AND CONCLUSIONS
The classic theories of the MNC sug-
gest that MNCs should have higher lev-
els of debt than DCs owing to the risk
reduction resulting from having opera-
tions in less than perfectly correlated
markets. However, research by Lee and
Kwok (1988) and Burgman (1996) con-
cludes that internationalization for US
firms actually leads to a reduction in
debt ratios, which they suggest stems
from MNCs' growth opportunities, in-
creased agency costs, and exchange rate
risks.
While agreeing that cross-country di-
versification benefits may play a role in
reducing corporate investment risks, this
research suggests that the dominant fac-
tor in explaining the overall impact of
internationalization on firm risk and le-
verage is the different risk classes of dif-
ferent countries. The results reported in
this study confirm the previous findings
that there is a debt reduction associated
with internationalization for US based
firms. However, for emerging market-
based firms, internationalization is sig-
nificantly associated with a positive in-
crease in leverage.
Further empirical analysis confirms
that as U.S. firms get more involved with
international investments, their total and
systematic risks tend to increase. In con-
trast, emerging market based firms have a
decrease in total and systematic risks as
they get more involved internationally.
In aggregate, the evidence suggests that
the MNC home/target market conditions
play an important role in predicting how
the firm's risks and capital structure
change with corporate internationaliza-
tion. The findings of this study are sum-
marized in Table 6. Consistent with ac-
cepted financial theory, the aggregate ev-
idence indicates an inverse relationship
between risk and leverage and is consis-
tent with the proposed upstream-down-
stream hypothesis.
In this study, the tests of relationships
among internationalization, total and
systematic risks, and MNCs' financial le-
verage are mostly conducted at the aggre-
TABLE6
INTERNATIONALIZATIONAND FINANCIALCHARACTERISTICSOF THEMNC:
A SUMMARY
Emerging
Regression EntireWorld IJSOnly Market
Leverage = AO + A1 FAR + controls + - +
Systematic Risk = A,, + Ap1FAR + controls Not Significant +
Total Risk = Bo + B1FAR + controls Not Significant +
This table provides a summary of the financial characteristicsfound associated with firm
internationalization.Each row gives the sign of the coefficient estimate associated with a
particulardata set regression (i.e. for A1 or Ap1or B.). The noted ? relationships are all
significantlv differentfromzero at various standardlevels as indicated in previous tables.
626 JOURNALOF INTERNATIONALBUSINESS STUDIES

CHUCKC.Y. KWOK,DAVID M. REEB
gate level. For future research, one may
empirically identify exactly what under-
lying factors lead to higher (lower) total
or systematic risks when MNCsstartop-
erations in foreign markets and how
these factorsaffect the MNCs'leverage.
NOTES
1. Our use of the term "emerging mar-
kets" follows that of the International
Monetary Fund's 1999 Capital Market
Report. Please see page 1 of their report
for their criteria. These countries are de-
noted with an asterisk in our Table 1.
2. There are of course other factors that
influence the risk of a project. Further-
more, it is not necessarily the case that a
project in an emerging market is riskier
than a project in a developed economy
and vice versa. However, we hypothe-
size that beyond the diversification ef-
fect, the relative stability of the two mar-
kets also plays a role in the riskiness of a
project and on the incremental impact
on firm systematic risk.
3. If the correlation coefficient is low,
it means that much of the increased
project risk in this volatile environment
is diversifiable in a portfolio context.
Then the systematic risk may not in-
crease or even decline.
4. Again, whether the beta will in-
crease or decrease depends on the
tradeoff between the correlation coeffi-
cient, Pim' and the project's total risk, i .
The net effect of these two factors should
be determined empirically.
5. An implicit assumption of our anal-
ysis is that emerging market firms are
able and do diversify into more stable
economies. Likewise our analysis also
assumes that stable economy based firms
diversify into less stable economies.
6. To ensure the effect of internation-
alization on risk and leverage, we in-
clude the level of capital market devel-
opment as a control in Equation (5) of
Table 5. After controlling for the'capital
market development, the effect of inter-
nationalization on leverage is still con-
sistent with the prediction of our up-
stream-downstreamhypothesis.
7. Since the data set we have does not
provide detail data of where individual
operations of an MNCare located (exact
matching of home and target markets),
we can only draw our conclusions based
on findings at the aggregatelevel.
8. The testing is repeated using the
foreign sales ratio for consistency with
previous research. The results lead to
similar inferences.
9. A potential concern with this ap-
proach is that MNCs could change the
types of debt they utilize in foreign mar-
kets. Therefore, the testing is repeated
using Total Liabilities/ (Total Liabili-
ties + MarketValue of Equity). The re-
sults lead to similar inferences.
10. Manyofthe observationshad miss-
ing returns.Repeatingthe analysis using
only firms with complete return data
lead to qualitatively similar results.
11. Specifically, Worldscope employs
approximately 120 multilingual finan-
cial analysts who utilize "detailed"
country-specific manuals that define
each data item so that "items are inter-
preted consistently'throughout all coun-
tries". Worldscope reports that they
closely examine the nature and compo-
nents of financial statements, notes to
accounts, and related disclosures, and
then rebuild the accounts on a compo-
nent basis. The standardized data is uti-
lized as it minimizes differences based
solely on financial reportingdifferences.
12. As one reviewer noted, the sample
may be the most complete available but
it still has only a limited number of
emerging marketfirms. The implication
is that the sample may not be represen-
VOL. 31, No. 4, FOURTHQUARTER, 2000 627

INTERNATIONALIZATIONAND FIRMRISK
tative of all emerging market based
MNCs and therefore care must be taken
in interpreting the results.
13. While outliers were detected (us-
ing R-Student statistic), their exclusion
did not lead to different inferences.
14. For a concise explanation of the
problems and remedies associated with
panel data, see Green (1997).
15. Many of the observations had miss-
ing returns. Repeating the analysis using
only firms with complete return data
lead to qualitatively similar results.
16. The findings reported in Tables 3-5
show significant associations between
internationalization and risks as well as
leverage; they do not indicate causality.
Our interpretation of the findings is
based on the theoretical argument in the
Third Section that internationalization
leads to the change of firm risk and there-
fore corporate leverage.
17. For consistency of table presenta-
tion, we use two-tailed tests to report the
level of significance in Tables 3-5. How-
ever, since we expect internationaliza-
tion is associated with lower risks and
higher leverage for MNCs from emerging
markets, one-tailed tests should be more
appropriate. In that case, the significance
level should actually be 0.05.
18. Fama and French (1992) suggest
two concerns in using firm betas. The
first concern is the beta is measured with
error and the second is that this error
may be correlated with some other vari-
ables in the equation. With our specifi-
cation, the primary concern is the former
and not the latter as we are using beta as
the dependent variable instead of as an
independent variable. Thus, the main
concern in our analysis is the increase in
the standard error associated with mea-
surement error in the dependent vari-
able.
19. The portfolio beta is estimated us-
ing the standard CAPM equation: rit =
rft + bi (rmt- rft) + et where rjt is the
random return on the ith portfolio at time
t, rftis the risk-free rate, bi is the measure
of systematic risk of portfolio i, rmtis the
world market return, and et is the mean
zero error term at time t.
20. The mean portfolio beta is .88 and
is consistent with the fact that the sam-
ple excluded firms with assets below
US$100 million.
21. Owing to the limited number of
portfolios from each region, running fur-
ther subset regressions is not practical.
22. Another potential concern is the
non-synchronous trading effect. How-
ever, our stringent sample selection pro-
cess minimizes this concern. For com-
pleteness, we repeat the systematic risk
regressions using the approach sug-
gested in Dimson (1979) to adjust for
non-synchronous trading. The results
are similar to those reported in Table V.
23. To control for the industry effect,
we use two dummy variables to repre-
sent the industries. We follow Harris and
Raviv (1991) to categorize industries into
three groups: those with low, medium,
and low debt. If the firm's industry falls
into the medium-debt group, the first in-
dustry dummy takes the value of 1. Al-
ternatively, if the firm's industry falls
into the high-debt group, the second in-
dustry dummy takes the value of 1. To
test the robustness of our results, two
other regressions are run: 1) using all 14
dummy variables to represent the 15 in-
dustries; and 2) leaving out the industry
control variables from the regression en-
tirely. Both regressions lead to similar
conclusions.
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