Global COE Hi-Stat Discussion Paper Series 046

Research Unit for Statisticaland Empirical Analysis in Social Sciences (Hi-Stat)

Vertical Foreign Direct Investment:
Evidence from Japanese and U.S. Multinational Enterprises

Hi-Stat Discussion Paper

Kiyoyasu Tanaka

March 2009

Hi-Stat
Institute of Economic Research
Hitotsubashi University
2-1 Naka, Kunitatchi Tokyo, 186-8601 Japan
http://gcoe.ier.hit-u.ac.jp

Vertical Foreign Direct Investment:
Evidence from Japanese and U.S. Multinational Enterprises
Kiyoyasu Tanaka*
Institute of Economic Research
Hitotsubashi University
Email: tanakak@ier.hit-u.ac.jp
May 23, 2009
Abstract
Foreign direct investment (FDI) has rapidly increased in developing countries for the 1990s, butformal evidence for vertical FDI has been surprisingly mixed. This paper empirically reconsiders
the factor-proportions hypothesis by exploring the role of host country’s relative skill
endowments in offshore production of multinational enterprises (MNEs). Using panel data onsales of foreign affiliates by Japanese and U.S. MNEs in the 1990s, I find that relative skill
abundance has a large negative impact on Japanese affiliate sales, but little effect on U.S. affiliate
sales. Robust to a wide variety of sensitivity checks, the results strongly support vertical FDI in
the case of Japanese MNEs, but not U.S. MNEs. Because the dominant view in favor ofhorizontal FDI against vertical FDI in the previous literature emerged primarily from U.S. data, I
empirically demonstrate that data sources on MNEs partly explain weak evidence for vertical
FDI.
Keywords: Multinational firm, foreign direct investment, skill endowment
JEL classification: F21, F23*

This paper is a substantially revised version of my dissertation chapter. I am deeply grateful tomy professors at the University of Hawaii at Manoa: Theresa Greaney, Sang-Hyop Lee, Ilan Noy,
Seiji Naya, and Jack Suyderhoud. I also thank to Jota Ishikawa, Toshiyuki Matsuura, andparticipants at One-Day Trade Workshop at Hitotsubashi University for valuable comments andsuggestions. All remaining errors are my own.

1. Introduction
The dramatic rise in foreign direct investment (FDI) is a prominent feature of economic
globalization, as global FDI flows increased at a faster pace than international trade and income
in recent decades. The global production of multinational enterprises (MNEs) accounted for an
estimated 10% of world output in 2006, as measured by the value-added of all foreign affiliates asa share of the world GDP (UNCTAD, 2006). It is commonly viewed among trade economists thatthe rise of multinational activity has been driven partly by a vertical type of FDI that is motivatedby low factor costs abroad. Accordingly, the factor-proportions models of international trade havebeen developed to explain why multinational firms establish production facilities in a low-wagecountry (Helpman, 1984; Helpman and Krugman, 1985; Markusen, 2002).
A growing number of studies have examined the empirical implication that vertical FDI
should arise when countries are different in relative factor endowments. Prior research, including
Carr et al. (2001), Braconier et al. (2005a), and Davies (2008), shows that multinational activity is
positively related to differences in relative skilled-labor abundance across countries, consistent
with vertical FDI. In contrast, another set of research such as Brainard (1993, 1997), Markusen
and Maskus (2001, 2002), and Blonigen et al. (2003), finds that multinational production isnegatively correlated with relative skill differences. Their findings are limited to supporting
horizontal FDI associated with market-access motives. Thus, econometric evidence for vertical
FDI is mixed and even contradictory, leading to the dominant view that FDI activity is primarily
horizontal. Despite the great interest in vertical fragmentation of production across borders, theempirical importance of the factor-seeking motive of multinational production remains largely
inconclusive.
The purpose of this paper is to reconsider the factor-proportions explanation for FDI byinvestigating the relationship between offshore production of multinational firms and relative skill
endowments of host countries. In this paper, I use panel data on sales of foreign affiliates byJapanese and U.S. MNEs for the years 1990, 1995, and 2000. A fairly consistent dataset on1

foreign affiliate sales allows for comparative assessment on the vertical motive of FDI acrossJapanese and U.S. multinational production in the same set of host countries. Furthermore, thispaper employs an instrumental-variables (IV) approach to address potential endogeneity of thehost-country supply of skilled labor, which is likely to underestimate vertical FDI. For instance,developing countries may have an incentive to upgrade skill levels of the labor force in order toattract foreign investment. Specifically, I exploit differences in past schooling characteristics as
instruments for the contemporaneous level of skilled-labor abundance measured by theeducational attainment of the labor force. Thus, I carefully take into account the endogeneity ofskilled-labor abundance to obtain a consistent estimate of the effect of skill endowments on
multinational activity.
Robust to a wide range of specifications and sensitivity checks, I find that skilled-laborabundance in foreign countries has a significantly negative impact on offshore production by
Japanese MNEs. The benchmark results predict that the real sales of Japanese affiliates inmanufacturing would decrease by 24.7% when the average years of schooling in host countries
increase by one year. For example, if the labor force in China possessed the equivalent level of
educational attainment as in the U.S. for the year 2000, Japanese affiliate sales in China would
have been negative, conditional on observables. This suggests that Japanese FDI was strongly
encouraged by the factor-cost motive. I also find that the IV estimates of the effect of relativeskill abundance are larger in magnitude than the standard regression estimates, implying that theendogeneity produces an upward bias in the estimated impact of host-country skilled-labor on
affiliate activities.
In stark contrast to Japanese MNEs, host-country relative skill endowments have nosignificant effect on foreign affiliate sales by U.S. MNEs. Even after accounting for theendogeneity bias that may underestimate the importance of vertical FDI, the factor-proportions
hypothesis is not supported in the U.S. sample. As host-country characteristics in the Japaneseand U.S. samples are virtually identical, the different conclusions on the vertical motive of FDI
2

are due to the different patterns of Japanese and U.S. multinational production; U.S. affiliate
activities are more concentrated in high-wage countries than Japanese affiliate activities. As
compared to prior work, my analysis empirically demonstrates that the data source ofmultinational activity plays a central role in driving empirical evidence for vertical FDI. The
implication is that the dominant view in favor of horizontal FDI in the previous literature could
result partly from the wide availability of U.S. data on multinational firms.
Section 2 reviews the related literature on vertical FDI. Section 3 discusses an empiricalstrategy in specification and estimation. Section 4 provides data descriptions of Japanese and U.S.
MNE activity and host-country characteristics. Section 5 presents the estimation results withsensitivity analysis. Section 6 concludes.

2. Empirical Literature on Vertical Foreign Direct Investment
This section first provides a brief summary of the general-equilibrium approach to FDI
to motivate the empirical literature on a vertical motive of multinational production. The
theoretical literature has traditionally focused on two forms of multinational production.1 Somefirms fragment the production process vertically across borders. These firms are vertical MNEs
that are headquartered in one country and produce in another country. Other firms establish an
identical production process abroad. These firms are horizontal MNEs that maintain both
headquarters and plant in one country and an additional plant in another country. Headquarters
services such as management, R&D, and advertising play a key role in supporting the operationof both MNEs.
A group of theoretical work such as Helpman (1984), Helpman and Krugman (1985),
and Markusen (2002) analyzes the role of factor-proportions differences in explaining the1

Theoretical papers discussed here abstract from the ownership decision of offshore plants. See
Helpman (2006) for a survey on international organization of production.
3

formation of vertical MNEs.2 These models predict that offshore production by vertical MNEs islikely to arise when countries are sufficiently different in factor proportions. To illustrate,consider two countries endowed with skilled and unskilled labor. Multinational firms consist ofheadquarters services and manufacturing production, with headquarters more skilled-labor
intensive than production. When countries are similar in relative skill endowments, cross-country
differences in the relative price of skilled to unskilled labor is eliminated by international trade.
There is no factor-cost incentive for firms in both countries to offshore a production plant.
When one country becomes sufficiently skilled-labor abundant relative to anothercountry, cross-border differentials in the relative skilled-labor cost is not equalized throughforeign trade. As a result, factor-cost differentials create an incentive for firms in a relatively
skilled-labor-abundant country to establish production facilities in a relatively skilled-labor-scarcecountry. Headquarters activity that uses skilled labor intensively is located in the country where
skilled labor is relatively cheap. Production activity that employs unskilled labor intensively is
moved to the country in which unskilled labor is relatively cheap. Consequently, vertical MNEs
arise in a single direction to serve consumers at home via offshore production solely because ofinternational differences in relative skill endowments. The supply of unskilled labor in the hostcountry plays a crucial role in attracting vertical investment from the skilled-labor-abundant
country.
Another set of theoretical work such as Markusen (1984), Brainard (1997), andMarkusen and Venables (1998, 2000), explores a firm’s decision between exporting and local
production in serving foreign markets to explain the formation of horizontal MNEs.3 In contrast
to vertical FDI, these models predict that horizontal FDI is likely to occur when countries are
similar in relative skill endowments. In these models, a firm consists of a headquarters and a
production plant at home. Factor intensities in headquarters and production activities are identical
2

Markusen (2002) combines both vertical and horizontal motives in the model, which is referred to as
the knowledge-capital model.
3
See Helpman et al. (2004) for the horizontal model that incorporates firm heterogeneity.
4

to rule out vertical fragmentation of production. The firm must decide whether to produce abroador export by comparing transportation costs of exporting and a plant-specific fixed cost for local
production. In the absence of factor-cost motives, horizontal MNEs will arise when gains from
economizing on trade costs offset an additional fixed cost of opening an overseas plant. Therefore,
the relative skill abundance in a host country provides no direct motive for horizontal FDI.4
While market-access and factor-seeking motives are equally prominent reasons for FDI
in theory, early empirical studies such as Brainard (1993, 1997), Ekholm (1998), Markusen and
Maskus (2001, 2002), provide little support for vertical FDI, but strong evidence in favor ofhorizontal FDI. Brainard (1993, 1997) investigates the market-access and factor-proportions
explanations of multinational production by exploring U.S. data on affiliate sales disaggregatedby country and industry for 1989. She finds that trade costs increase affiliate sales both absolutely
and relative to trade, but cross-country differentials in income per worker reduce affiliate
activities. Ekholm (1998) provides similar evidence from country-level data on affiliate sales of
Swedish multinationals in 1994. Furthermore, Markusen and Maskus (2001, 2002) explicitly test
the vertical model against the horizontal model for U.S. data on affiliate sales at the country levelfor 1986-1994. They find that skilled-labor abundance in the host country increases both local andexport sales by U.S. affiliates. These findings suggest that horizontal investment is far more
important than vertical investment in accounting for aggregate multinational activity.
Aggregate multinational sales arise from both vertical and horizontal reasons for FDI
that interact in a complex way. Based on the knowledge-capital model of horizontal and vertical
MNEs, Carr et al. (2001) estimate an empirical specification that accounts for complex effects ofcountry characteristics. Using the panel data as in Markusen and Maskus (2002), they find that
affiliate production of U.S. firms is attracted to skilled-labor-abundant countries. Blonigen et al.
(2003) estimate the modified empirical specification of Carr et al. for U.S. and OECD samples of

4

Markusen (2002) shows that factor-cost differentials indirectly discourage horizontal MNEs,
because firms favor exporting over local production for sale in a high-cost market.
5

MNE activity with the larger country coverage. They show that absolute differences in relativeskill endowments reduce affiliate and FDI activity. These results are also inconsistent with thefactor-proportions explanation, even after controlling for horizontal reasons.
In response to the dominant evidence for horizontal FDI, a growing number of empiricalstudies have taken various empirical strategies in search of vertical FDI. A set of empirical work
attempts to resolve mixed evidence of the vertical part of the knowledge-capital model. Braconier
et al. (2005a) and Davies (2008) modify the empirical specification of Carr et al. and enlarge thecountry coverage of the MNE data. While these studies provide some evidence for vertical MNEs,
their results are sensitive in the sense that relative skill abundance has statistically insignificant
effects on FDI activity in some specifications. Another empirical strategy is to directly measureinternational differences in unskilled labor costs. Braconier, Norbäck, and Urban (2005b) focus
on cross-country differences in wage costs by skill level in explaining various affiliate activities
of U.S. and Swedish multinationals for 1986-1994. They find that the various types of affiliate
production are attracted to a low-wage country for unskilled labor. Hanson, Mataloni, andSlaughter (2005) study trade in intermediate inputs for further processing between foreign
affiliates and their parent firms. Using a firm-level sample on U.S. multinationals in 1994, theyshow that affiliate demand for imported inputs is higher in a country with low unskilled-labor cost.
While these findings accord with the factor-proportions implications, it is puzzling that bothstudies show a positive impact of host-country skilled-labor costs on affiliate activities.
Hanson, Mataloni, and Slaughter (2001) describe a wide range of affiliate activities
from detailed information on U.S. multinationals for the years 1982, 1989, and 1998. They
present the evidence that trade by foreign affiliates grew in specific countries (Canada and
Mexico) and industries (machinery and electronics equipments) for the 1990s. Using a 1994
sample on foreign affiliates by U.S. firms, Yeaple (2003) shows that multinational production inless-skill-intensive sectors is attracted to skilled-labor-scarce countries. These findings support
the presence of comparative advantage motives for U.S. outward FDI. To extend the previous
6

work that concentrates on U.S. MNEs, Alfaro and Charlton (2007) use a global dataset on foreignsubsidiaries in 90 countries and 400 industries. They define vertical FDI as a plant owned by aforeign firm that provides intermediate inputs to its parent firm, and horizontal FDI as a plant thatbelongs to the same product code as its parent firm.5 They find that subsidiaries previouslyclassified as horizontal FDI at the 2-digit industry level are in fact vertical FDI at the 4 digit level;
foreign subsidiaries in the specialized input sector for their parents are prevalent in number acrossdeveloped countries. However, they are not able to observe a trade link between affiliates andparents for a lack of information on affiliate exports. The subsidiaries defined as vertical FDI intheir work could actually supply inputs primarily to local producers. In this case, offshore
production arises for market-access, rather than factor-seeking, reasons.
This paper adds to the empirical literature in two ways. First, I combine country-level
panel data on sales by foreign affiliates of Japanese parent firms with existing U.S. data. Offshore
production by Japanese and U.S. MNEs, both of which are headquartered in large and skill
abundant countries, are measured in a fairly consistent way. By using an identical group of hostcountries, this dataset allows for an international comparison on the importance of vertical FDI
across Japanese and U.S. MNEs. Since influential papers such as Brainard, (1997), Carr et al.
(2001), and Yeaple (2003) draw conclusions almost exclusively from U.S. data, my work
provides an important check on possible influences of the U.S. data source in previous evidence
against vertical FDI.
Second, this paper improves an empirical strategy on factor-seeking FDI. While manyof previous studies exploit a variation in skilled-labor abundance to estimate the factor-cost
motive of multinational production, they have paid little attention to a possible bias of theestimated effects of relative skill endowments on MNE activity. It was often (implicitly) assumed

5

Based on the definition of industry classification, the subsidiaries that assemble final goods forexport to their parents are likely to be in the same product code as the parents. Despite the verticalnature of such affiliate activity, these subsidiaries seem to be classified as horizontal FDI in theirwork.
7

that country-level skill endowments are measured with little error and exogenously determined to
identify the parameters of interest. Apparently, there are a number of reasons to indicate thepresence of possible bias in the previous estimates for the violation of the assumptions, which is
discussed in section 3. Therefore, this study carefully takes into account the potential endogeneityof skill endowments in a host country by exploiting a variation in some measures of pastschooling characteristics as an instrument for the contemporaneous level of educational
attainment.

3. Empirical Framework
3.1. Empirical Specification
To analyze the factor-proportions theory, I adopt an empirical specification designed toestimate the knowledge-capital model in Carr et al. (2001). Their estimating equation is specified
to explain affiliate production as a function of home- and host-country characteristics. While thespecification includes differences in relative skill endowments to study a vertical motive ofmultinational activity, it must be modified to meet the nature of my dataset. Since my dataset has
only two parent countries, Japan and the U.S., there is little variation in home-country relativeskill endowments. Data on the host country account for the dominant variation in relative skill
differences across countries. There is little advantage to consider parent-country skill endowments.
Focusing on host country’s relative skill abundance, I estimate the following equation separately
for the Japanese and U.S. samples with a host country i and year t:
ASALEit = β0 + β1SKILLit + ηXit + ΣtγtTt + εit(1)

ASALE is the real volume of aggregate sales by manufacturing affiliates in each host country, withmore than 10 % of their equity stakes owned by parent firms in a home country. SKILL is themeasure of the relative supply of skilled labor in each host country. X is a vector of independent
variables that include important host-country characteristics in the investment decision by parent8

firms. These variables serve to disentangle the effects of skill endowments on multinational
production from potentially relevant determinants. Tt is a set of time fixed effects, with γt a vectorof the coefficients. Finally, ε is an error term.
The purpose of this paper is to obtain an estimate of β1 in the estimating equation fordata on Japanese and U.S. MNEs. The central hypothesis from the factor-proportions model of
FDI is that if multinational production is motivated to take advantage of factor-price differentials
across borders, then multinational firms would prefer to locate their offshore production in
unskilled-labor-abundant countries. Labor-intensive stages of production such as final assembly
are moved to a host country that has the lower cost of unskilled workers relative to skilledworkers than does a parent country. This implies that affiliate sales should be negatively
associated with the skilled-labor abundance in a host country. In other words, a negative sign ofthe estimate of β1 shows evidence for vertical FDI.
The alternative hypothesis derived from the market-access explanation for FDI is that if
multinationals invest abroad to obtain the access to foreign markets, then factor-cost differentials
have no direct impact on the location of their offshore production. The formation of horizontal
MNEs is driven not by labor-cost differentials, but by high trade barriers and the large market size.
Affiliate sales should not be correlated with the host country’s relative skill endowments. In thecase of multinationals from highly skill-abundant countries such as Japan and the U.S., a larger
value of SKILL implies convergence in relative skill abundance across countries. Skilled-laborabundance could have a positive impact on affiliate sales if horizontal motives are present in data.
Thus, a nonnegative sign of the estimate of β1 can be suggesting evidence for the alternative
hypothesis in favor of horizontal FDI.
A set of independent variables, X, are included in equation (1) to control for the otherattractiveness of the host market in the location of multinational production. Following Carr et al.
(2001), I account for the variables such as GDP, MKP, DIST, TC, and IC. GDP is the level of real
GDP in a host country. As firms prefer to locate offshore production in the large market for sale,9the predict sign for GDP is positive. MKP captures the potential opportunity to export to third
markets from a foreign country. If the market potential attracts foreign firms as anexport-platform base, MKP would have a positive impact on affiliate sales. On the other hand, if
MKP simply reflects the attractiveness of neighboring markets relative to the host country,
multinationals may avoid to locate production in the host country with large market potential.
MKP would have a negative impact on affiliate sales. The expected sign of MKP is ambiguous.
DIST is the geographic distance between capital cities in home and host countries. Since
the distance is a proxy not only for transport costs between countries, but for information andmonitoring costs on business operations in the foreign country, the expected sign of DIST is
unclear. TC is inward trade cost for measuring trade barriers to imports in a host country. If thedata are consistent with horizontal MNEs that economize on trading costs by overseas production,
TC should have the positive sign. If the data are consistent with vertical MNEs that supply inputs
to foreign assembly, TC should have the negative sign. The predicted sign of TC is not clear.
Lastly, IC is investment cost to represent overall investment climate in a host country. As highinvestment barriers deter the entry of foreign firms to a host market, the predict sign of IC isnegative.

3.2. Estimation Strategy
The empirical model as specified in equation (1) allows me to disentangle the effects ofrelative skill endowments on multinational production from those of a wide variety of othercountry determinants. More precisely, regression analysis with ordinary least squares (OLS)
provides an estimate of the coefficient of SKILL, conditional on observable factors such as market
opportunities, trade barriers, and investment risk. This paper attempts to shed light on causal
effects of skill endowments on multinational production by exploiting a variation in pastschooling characteristics as an instrument for the contemporaneous level of host-country skill
endowments. This estimation strategy is useful not only for obtaining a consistent estimate of the10coefficient of SKILL, but for reconsidering a potential bias in previous findings on vertical FDI.
Following the exposition of Wooldridge (2002), SKILL is an endogenous variable when
SKILL is correlated with an error term in equation (1). Assuming that available data on relativeskill endowments are generated independently from unobserved factors, many of previous
empirical studies analyze the linkage between skilled-labor abundance and multinational activity.
However, there are a host of reasons to suspect the possible violation of the assumption, which
would lead to inconsistency in linear regression. First, reverse causality arises if the supply ofskilled labor in a foreign country is affected partly by multinational activity. Slaughter (2002)
illustrates several channels through which inward FDI can contribute to skill improvements in thedeveloping countries. The growth of FDI activity since the late 1980s coincided with increased
schooling in many developing countries (Barro and Lee, 2000), possibly suggesting an incentive
effect of a perceived benefit of FDI on investment in human capital.
Second, measurement error occurs when a proxy variable for skilled-labor abundance
includes errors that are correlated with the proxy, but not with the unobserved SKILL variable.
Given the tremendous difficulty in practice to make a distinction between skilled and unskilledworkers both within and across countries, it follows that the available data for SKILL are likely to
be measured with substantial errors. Attenuation bias from the measurement error can reduce thestatistical significance of the coefficient of SKILL, which gives rise to bias in favor of horizontal
FDI. Finally, omitted-variables bias appears when an error term contains additional variables thatare correlated with SKILL. There may be unobserved forms of economic institutions such as arule of law that create favorable investment climate for foreign investors as well as promotesound development of education systems. As a result, the estimated coefficient of SKILL can bebiased upward. While it is difficult to pin down a crucial source of the endogeneity problem
among others, it is reasonable to suspect that the SKILL variable suffers from any of possible
forms of the endogeneity.
To solve the endogeneity problem, I employ the instrumental-variables (IV) estimation
11

with past schooling characteristics as a set of instruments for the current skill intensity of thelabor force in a host country. Specifically, I estimate a reduced-form equation for SKILL as
follows.
SKILLit = δ0 + δ1PSCHOOLi, t-10 + δ2SSCHOOLi, t-10 + λXit + ΣtμtTt + vit(2)

PSCHOOL and SSCHOOL are the average years of primary and secondary schooling of people
over age 25 in the previous 10 years, respectively. In the first step, equation (2) is estimated with
OLS to obtain the fitted value of SKILL. In the second step, SKILL in equation (1) is replacedwith the fitted values of SKILL from the first step, and then the modified equation (1) is estimatedwith OLS to obtain a consistent estimate of the coefficient of SKILL in the presence of theendogeneity problem.
It is in order to discuss two key assumptions required to identify equation (1) with theIV estimator. First, at least one of the two instruments, PSCHOOL and SSCHOOL, must be
sufficiently correlated with SKILL. Conceptually, it is reasonable that the relative supply ofskilled labor in a country can be measured with the aggregate stock of human capital obtained
through education, which is available for production activities by multinationals. If the average
years of schooling are longer for the average adult individuals in one country than for those inanother country, then the country is more skilled-labor abundant relative to another country.
Given that human capital stock obtained at school represents the abundance of skilled labor, thepast level of educational attainment of the population is the best predictor of the current level of
educational attainment. Cross-country differences in the average length of schooling in the past
period should be reasonably linked to differences in relative skill endowments across countries in
the current period.
Specifically, I employ the 10-year previous level of the average years of primary andsecondary schooling for the contemporaneous level of the average years of schooling.6 This6

The 5-year previous level of primary and secondary schooling gives similar results.
12indicates that if the average persons in one country have already spent a longer time at primaryand secondary levels than those in another country this year, then the average length of schoolingis likely to be longer in the country than in another country in 10 years. Thus, the choice of
instruments is based on a conceptually valid link between schooling and SKILL. In addition, it isalso crucial in empirical analysis to assess a correlation between the instruments and thepotentially endogenous variable. Following Bound, Jaeger, and Baker (1995), I examine
instrument relevance by the partial R-squared measures and the F test of the joint significance of
PSCHOOL and SSCHOOL in the first-stage regression. A high value of the partial R-squared anda low p-value of the F statistics would be evidence for the instrument relevance.
Second, a set of the instruments must be uncorrelated with an error term in equation (1).
The exclusion restriction implied by IV regression is that educational attainment obtained atprimary and secondary schools 10 years ago, conditional on the included control variables, haveno impact on multinational activity this year. The instruments can have effects on affiliate sales
only through skilled-labor endowments. A potential concern is that the past level of primary andsecondary schooling of the population could be correlated with the current unobserved
characteristics of the host country, which may have a significant direct effect on multinational
activity. To the extent that other transmission channels could work, the IV estimate of the effectsof SKILL on affiliate sales would capture partly an indirect effect of other determinants. Because
the presence of the other transmission channels is not readily apparent, it is not conceptuallypossible to reject the unintended consequences of the concern about the exclusion restriction.
Nevertheless, it is possible to assess the second criterion that the instruments are sufficiently
irrelevant to an error term in equation (1) by testing overidentifying restrictions with the J statisticof Hansen (1982). Under the null hypothesis that the instruments are uncorrelated with the error
term, the failure to reject the null would provide a check on the instrument irrelevance.

13

4. Data Description
4.1. Data on Foreign-Affiliate Activity of Japanese and U.S. firms
To study a link between outward FDI and skill endowments, this paper uses data on
foreign affiliates by Japanese and U.S. parent firms.7 The data on Japanese affiliates are takenfrom the survey on overseas business activities of Japanese firms conducted annually by the
Ministry of Economy, Trade, and Industry (METI) in Japan. To examine the stylized facts on
Japanese affiliate activities, the METI sends the survey questionnaire directly to the firms that areheadquartered in Japan and own more than 10% of shares of the business enterprise in a foreigncountry. While the survey covers both manufacturing and non-manufacturing sectors, it excludes
parent firms in the finance, insurance, and real estate sectors. A wide variety of data items areincluded in the survey to measure foreign affiliate characteristics such as country and industry
codes, sales and purchases by destination, and employment.
While the METI survey provides detailed information on Japanese multinational
activities, it has been recognized that the survey results suffer from low response rates of around60%, varying samples of parent firms over time, and widely fluctuating sales at the affiliate level.
These issues result partly from the fact that reporting to the METI survey is not mandatory forparent firms. The publicly available data provided by the METI are neither sufficiently
comparable to foreign-affiliate data from other country sources nor appropriate for rigorous
econometric analysis. To overcome dirty data problems, I use the improved data of the METI
survey from the Research Institute of Economy, Trade, and Industry (RIETI).8 More specifically,
Matsuura (2004) exploits individual questionnaires reported by Japanese parent firms to constructpanel data on affiliate sales, purchases, and employment at the foreign-affiliate level acrosscountries and industries for the period 1989-2002. After identifying parent and affiliate firms,
sector codes, and entry and exit of foreign affiliates in the data, he estimates the missing
7

Data on FDI flows and stocks are more widely available than affiliate data, but imperfect indicatorof multinational production with which the factor-proportions hypothesis is concerned.
8
The RIETI data are available at http://www.rieti.go.jp/database/d08.html.
14observations by linear extrapolation for each affiliate. The RIETI provides public access toaffiliate data aggregated by country, industry, and year.
For comparison of foreign production by Japanese multinationals with that by U.S.
multinationals, I exploit data on foreign affiliates of U.S. nonbank firms from the survey of U.S.
direct investment abroad published by the U.S. Bureau of Economics Analysis (BEA).
Benchmark surveys are conducted every five years to obtain comprehensive data on all foreign
affiliates of U.S. firms. While sample surveys in the non-benchmark years exempt small firms
from filing a survey to reduce their reporting burden, the BEA keeps the affiliate coverage overtime by estimating their affiliate activities. The BEA survey defines a foreign affiliate as anoverseas business enterprise in which a single U.S. firm or person owns 10% or more of thevoting securities. A foreign affiliate is assigned to the sector in which it has the largest percentage
of its sales. The BEA provides a number of tabulations on various data items on foreign affiliates
aggregated by country and industry.
This paper takes data on foreign affiliate sales from the RIETI and BEA. The data are
aggregated over manufacturing sectors to the country level for exploring the relationship between
manufacturing production by multinationals and unskilled-labor supply in a host country. Because
affiliate sales are denominated in Japanese Yen for the RIETI data and in U.S. dollar for the BEA
data, affiliate activities are not directly comparable across these data sources. Thus, Japaneseaffiliate sales are measured in millions of U.S. dollars using the average of Yen-dollar annual
exchange rates in the 1989-2002 period, taken from the International Financial Statistics (IFS) of
the International Monetary Fund.9 Another issue is that affiliate sales denominated in nominal
U.S. dollars are influenced by annual inflation rates. A variation in affiliate sales includes both achange in the price level and a change in real economic activity of foreign affiliates. Thus,
affiliate sales are measured in year 2000 U.S. dollars using a U.S. wholesale price index of IFS.

9

The period average of exchange rates is used to mitigate an influence from large annual movements
in Yen-denominated value of one dollar.
15

Since the RIETI and BEA survey foreign affiliate activities in a similar way as toconcepts and definitions, both datasets provide a fairly consistent measure of real manufacturing
production of foreign subsidiaries by Japanese and U.S. MNEs. Compared to statistics on FDI
flows and stocks, the affiliate data are much more appropriate for empirical analysis on the scaleof the foreign operations of vertical MNEs as predicted by the factor-proportions models.
However, it is also important to check practical consistency between the data sources. For thispurpose, I compare real sales by Japanese manufacturing affiliates in the U.S. from the RIETI
source with those from the U.S. BEA’s Foreign Direct Investment in the United States. Although
the time-series plots show that Japanese affiliate sales are not identical between the RIETI and
BEA data for the period 1989-2002, both data exhibit significantly similar movements in annualchanges of affiliate sales, with a correlation coefficient of 0.93.10 Thus, the result supports
consistency across data sources on Japanese and U.S. multinational activities.

4.2. Data on Host-country Characteristics
This paper explores the factor-proportions hypothesis in explaining the pattern ofJapanese and U.S. multinational production. While there are various indicators of a country’s
factor proportions such as capital, labor, and arable land, relative factor endowment is measured
by the proportion of skilled labor in the total labor force. Skilled-labor abundance is previously
used as a key variable to investigate the relative importance of vertical FDI relative to horizontal
FDI. Since it is difficult to disentangle skilled labor from unskilled labor in each country, relativeskilled-labor abundance is measured by the educational attainment from Barro and Lee (2000).11

10

Although affiliate sales by the RIETI data are higher than those by the BEA data, a systematicdifference appears to result from original survey methods. Specifically, BEA survey defines a foreign
affiliate owned by a single U.S. firm whereas the METI survey defines a foreign affiliate owned either
by a single Japanese firm or jointly by a Japanese parent firm and its other foreign affiliate. In addition,a foreign-affiliate’s industry is determined by sectoral sales of the affiliate in the BEA survey, but by
subjective judgment of a person who files a report in the METI survey.
11
Another data source is occupational employment statistics published by the International Labor
Organization (ILO). However, the ILO data are less consistent for an international comparison because
16Barro and Lee’s dataset is constructed by improving census/survey data on schooling from anumber of countries in consistent methodology. An improved measure of human capital stock
obtained through education with the wide country coverage is extensively used in the literature.
Specifically, this paper measures skilled-labor abundance with the average years ofschooling of people over age 25. However, the education data are available only for every 5 year
over the period 1960-2000 whereas MNE data cover the period 1989-2002. The data availability
forces me to exploit a variation in educational attainment across countries for the years 1990,
1995, and 2000.12 Additionally, I exploit previous schooling characteristics as instruments for thecontemporaneous level of relative skill abundance. Data on past schooling are the average years
of primary and secondary schooling of people over age 25 in the previous 10 years from Barroand Lee.
The following data on host-country characteristics are also used. Data on real GDP
measured in billions of year 2000 U.S. dollars are taken from the World Development
Indicators.13 Data on distance measured in kilometers between capital cities of home and hostcountries come from the International Trade Data website of Raymond Robertson (formerly
maintained by Jon Haveman). For data on trade barriers, I use a survey index of national
protectionism on imports from the World Competitiveness Report (the World Competitiveness
Yearbook for 2000 data) by the International Institute of Management Development. The index
ranges from zero to 100, with a higher number indicating greater perceived trade costs bycorporate executives. Finally, data on investment risk in a country are obtained from Euromoney.
The risk score is composed of 9 weighted individual scores on investment environment; politicalsome countries report employment in the 1968 International Standard Classification of Occupations(ISCO) and other countries in the 1988 ISCO. Occupational categories are defined in very different
concepts across the schemes, and some countries even switch the reporting scheme in the period of myinterest.
12
Although annual levels in educational attainment can be created by linear interpolation between
available years, this method provides little additional variation in skill endowment for regression
analysis.
13
Taiwan GDP data are taken from the Department of Commerce, Taiwan.
17risk (25%), economic performance (25%), debt indicators (10%), debt in default or rescheduled(10%), credit ratings (10%), access to bank finance (5%), access to short-term finance (5%),
access to capital markets (5%), and discount on forfaiting (5%), with higher scores indicating
higher country risk.

4.3. Descriptive Statistics
Table 1 presents summary statistics of the Japanese and U.S. samples for regression
analysis.14 There are 110 and 98 observations for the Japanese and U.S. samples, respectively.
The difference in the number of observations is partly due to the fact that the data cover 41 hostcountries for Japanese MNEs and 39 host countries for U.S. MNEs. The U.S. data do not include
such countries as Greece, Hungary, and the U.S. for host countries of U.S. affiliates. The Japanesesample excludes Japan as a host country. Because the following results are not affected byincluding those countries in analysis, the larger samples are used to obtain more efficientestimates. The summary statistics clearly present two key characteristics of my dataset. First, thedistribution of foreign affiliate sales is significantly different for Japanese and U.S. multinationals.
Second, the host-country characteristics such as relative skill endowments, market size, andinward trade costs are almost identical across the Japanese and U.S. samples. These
characteristics imply that any difference in descriptive and econometric analysis across theJapanese and U.S. samples will result primarily from the nature of foreign production by Japaneseand U.S. MNEs.
[Table 1 around here]
Since affiliate data play a key role in the following results, I characterize a pattern ofJapanese and U.S. multinational activity with box plots on foreign-affiliate sales for the years
1990, 1995, and 2000. Figure 1 provides additional information on the distribution of affiliate
14

The Appendix contains a list of variable definition and data source, and a list of host countries.
18

sales to make comparison for an international pattern of Japanese and U.S. multinational activities.
There are two prominent features in the figure. The first feature is the wide gap between the
maximum and minimum volumes of Japanese affiliate sales, as compared to those of U.S.
affiliate sales. This feature indicates that Japanese MNEs have the more dispersed presence of
foreign production across countries than do U.S. MNEs. Second, the median values of theJapanese affiliate sales are smaller than those of the U.S. affiliate sales across the years,
suggesting that the presence of Japanese MNEs in foreign markets is smaller than that of U.S.
MNEs. In other words, U.S. multinationals maintain the deeper and more concentrated presenceof foreign production than do Japanese MNEs.
[Figure 1 around here]
Before proceeding with formal econometric analysis, I illustrate the cross-country
pattern of multinational activity and relative skill endowments for Japanese and U.S. MNEs.
Figures 2-4 presents a relationship between the natural logarithm of affiliate sales relative to GDP
and the average years of schooling of the labor force for the years 1990, 1995, and 2000,
respectively. Because the volume of multinational sales is strongly influenced by a scale effect of
the country size, affiliate activity at the vertical axis is measured by the relative presence ofaffiliate production in the host economy. All of these figures clearly show a negative relationshipbetween affiliate sales and educational attainment for the Japanese sample, but a positive
relationship for the U.S. sample. These results indicate that affiliate sales by Japanesemultinationals are relatively larger in more unskilled-labor-abundant countries, consistent withthe empirical implication of the factor-proportions hypothesis on vertical MNE activity. In
contrast, affiliate sales by U.S. multinationals are relatively larger in more skilled-labor-abundant
countries, suggesting that foreign production by U.S. firms is attracted to skilled labor. Because
the U.S. is one of the most skill abundant countries, the figures imply that U.S. multinational
activity is larger when the U.S. and host countries are similar in relative skill endowments. Thus,
19the U.S. data support the model of horizontal FDI in terms of relative endowments.
[Figure 2-4 around here]
In sum, a simple correlation in the data suggests that Japanese firms may have invested
abroad to take advantage of factor-cost differentials across countries whereas U.S. firms may nothave established offshore production strongly for factor-cost motives. Evidence for vertical FDI isfound in the case of Japanese MNEs, but not U.S. MNEs. It is worthwhile to note that theconclusion is drawn from using the share of affiliate sales in GDP levels as a measure ofmultinational activity. Defining the variable in such a way is almost equivalent to exploring therole of skill endowments in the cross-country pattern of affiliate sales after controlling for themarket-size effects. Obviously, there are a number of other determinants of multinational activity
such as trade barriers, investment climate, and government policy. The observed correlation
between affiliate sales and education attainment may simply be confounded by omitted third
factors. It is a task in the next section to disentangle the effects of skill endowments from othercountry determinants.

5. Estimation Results
5.1. OLS Regression
Table 2 presents the results of OLS regression on the determinants of Japanese and U.S.
multinational activity. The dependent variable is the natural logarithm of the real volume of sales
by manufacturing foreign affiliates of multinationals. The panel data used in estimation include
the years 1990, 1995, and 2000 for the Japanese and U.S. samples. The panel dataset isunbalanced for missing observations of some of the independent variables. 15 Since a15

Trade cost in a host country has the slightly small country coverage in early years. While excluding
the trade-cost variable from the model increases the host-country samples in regression, it is likely tointroduce an omitted-variables bias in OLS estimates of the effects of skill endowments on MNE
activity. As Carr et al. (2001) use the same survey measure for inward trade barriers, I choose the20Breusch-Pagan test for initial OLS regressions indicates the presence of heteroskedasticity, thefollowing regression results report heteroskedasticity-consistent standard errors.
[Table 2 around here]
Column (1) shows the OLS results for the sample on Japanese MNEs. As suggested by
the descriptive analysis, OLS regression gives a significantly negative estimate of the coefficientof host-country skill endowments. This implies that foreign affiliate sales by Japanese firms arelikely to decrease with skilled-labor abundance in host countries, conditional on the otherobservable determinants. In other words, the host country’s supply of unskilled-labor would
encourage foreign production by Japanese MNEs, consistent with the prediction of thefactor-proportions hypothesis. Because the skill-endowment variable is measured by the average
years of schooling in the population for the dependent variable of the log of affiliate sales, the sizeof the coefficient implies that Japanese affiliate sales are predicted to decrease by 24.7% when the
average person in a host country increases the schooling by one more year.16 For instance, theaverage educational attainment for the year 2000 is around 6 years in China and 12 years in the
U.S. If China had achieved 6 more years of schooling equivalent to the U.S. level, Japaneseaffiliate sales were predicted to decrease by whopping 148.2%. Since Japanese affiliates in China
had their sales of about 28 billions in U.S. dollar, the calculation implies that the whole volume of
their sales could have even disappeared in a ceteris paribus sense.
In contrast to the OLS results for Japanese MNEs, column (2) shows that the relative
supply of skilled labor has a statistically insignificant coefficient in OLS specification. Anychange in the host country’s abundance of skilled labor has no effect on foreign affiliate sales by
U.S. firms. As briefly discussed in the literature review, an alternative explanation for the
possible loss of efficiency from overspecification instead of the possible bias of the estimates fromunderspecification.
16
The marginal effect is computed by 100×(exp(-0.284)-1), which is equal to -24.7. Taking into
account standard errors of the coefficient, the population parameter would range between -0.11 and-0.45 for 95% of the samples. This indicates that the marginal effect could lie between -10.4 to -36.2.
21

formation of MNE activity against vertical FDI is that horizontal MNEs arise when there are
relatively large marginal costs in exporting and lower fixed costs in local production, suggesting
no direct role of skill endowments in the location of affiliate production. The U.S. sample isconsistent with these implications of horizontal FDI, but provides no support for vertical FDI. The
OLS results for U.S. MNE activity also accord well with the previous findings such as Brainard(1997), Carr et al. (2001), and Blonigen et al. (2003). Using the BEA data on outward U.S.
affiliate sales in the 1980s and early 1990s, these authors tend to find that U.S. multinationals are
attracted to skilled-labor-abundant foreign countries. Since I extend the period coverage up to
year 2000, my findings possibly imply that skill abundance became largely irrelevant for thelocation of more recent U.S. outward FDI.
To statistically test a difference in the coefficients of skill endowments across Japaneseand U.S. samples, I include the specification with interaction terms between independent
variables and a dummy variable for Japanese MNEs, with the latter entering the model
independently. For brevity, column (3) shows only the coefficients of the interaction terms fromthe new specification estimated with OLS for a pooled sample. As expected from the separate
sample regressions, the coefficient of skill endowments in the Japanese sample is smaller by 0.3
than that in the U.S. sample. The test for coefficient differences shows that host-country skill
endowments have significantly different impacts on Japanese and U.S. affiliate sales. Combining
with the results for the separate samples, it is suggested that Japanese multinationals prefer tolocate offshore production in unskilled-labor-abundant countries more strongly than do U.S.
multinationals. Although relative skill abundance has no significant influences on the location of
U.S. multinational production, U.S. MNEs tend to locate overseas production in moreskilled-labor-abundant countries as compared to Japanese MNEs.
Table 2 provides additional insights on important host-country characteristics for
multinational production. GDP has the significantly positive coefficients for both Japanese andU.S. data. Offshore production by Japanese and U.S. multinationals is attracted to the large
22market primarily for serving local consumers. Market potential has the significantly negative
coefficient in the Japanese sample, indicating that Japanese MNEs tend to avoid the location withpotentially large exporting opportunities from a host country. It may simply mean that ifneighboring countries are relatively large in economic size, Japanese firms would establish
foreign production in the neighboring countries. The coefficients of geographic distance are
significantly negative for both Japanese and U.S. data. Multinationals prefer host countries close
to their parent countries for various reasons such as information and transportation costs. Tradeand investment costs have the negative coefficients, but the statistical significance varies acrossthe samples.

5.2. Instrumental Variables Regression
The empirical analysis up to this point has suggested that relative skill abundance inhost countries is negatively correlated with Japanese affiliate sales, but has little association with
U.S. affiliate sales. These findings are generally consistent with vertical FDI in the case of Japanand with horizontal FDI in the case of the U.S. However, as discussed in the estimation strategy,
these results are not sufficient to conclude that host country’s unskilled labor plays a causal role inattracting Japanese affiliate activities. The causality link of skill endowments and affiliate
production can break down for a number of econometric issues. A possible endogeneity of the
SKILL variable in OLS regression is the major concern for analysis. Thus, this section addresses
the endogeneity issue by exploiting cross-country differences in past schooling characteristics as
instruments for the current skill endowments. If test statistics support instrument relevance for an
endogenous variable and its irrelevance for an error term of the structural model, it is reasonable
to interpret a significantly negative coefficient of SKILL as suggesting a causal effect of
unskilled-labor abundance on MNE activity.
Table 3 presents the results of IV regression for Japanese and U.S. multinational activity.
In the case of the Japanese sample, column (1) shows the second-stage regression for the equation23

(1) that replaces SKILL with the fitted value of SKILL in the first-stage regression of column (2).
The IV estimate of the coefficient of SKILL is significantly negative with the slightly larger
absolute size of the coefficient as compared to the OLS estimate. Taking into account possible
bias in the OLS estimate arising from the endogeneity problem, the IV regression suggests thatskilled-labor endowments could have stronger negative impacts on Japanese affiliate sales thanwhat implied by the OLS specification.
To check the validity of the IV specification, the first-stage regression supports
instrument relevance of the average years of primary and secondary schooling in the previous 10
year. These instruments enter with high significance both individually and jointly in the first-stage
regression. The partial R-squared of 0.88 strongly indicates a high correlation between the SKILL
variable and the instruments. This implies that potential bias resulting from weak instruments is
not a concern in the IV regression. In addition, instrument irrelevance in the structural equation is
supported by the relatively small value of Hansen’s J statistics for the overidentification test. In
other words, there is no strong evidence that the exogenous variables are correlated with theresiduals from the second-stage regression. Thus, all of these findings lend considerable support
to the conclusion that unskilled-labor abundance in host markets has the significant causality
effect on offshore production by Japanese MNEs.
[Table 3 around here]
The IV regression for the U.S. sample is shown in columns (3) and (4). The IV estimateof the coefficient of SKILL is negative, but statistically insignificant. Compared to the OLS
estimate, the IV estimate implies that the potential endogeneity of the SKILL variable has an
upward pressure on the effect of host-country skill endowments on U.S. affiliate sales.
Nevertheless, there is little evidence that foreign unskilled-labor plays a role in the location of
U.S. multinational activity. As the tests support instrument relevance in the Japanese sample, theinstruments are highly correlated with the SKILL variable in the U.S. regression. In contrast, the24relatively large value of the Hansen’s J statistics does not show the absence of the endogeneity.
However, the Hansen test needs to be interpreted with care. As discussed in Hayashi(2000, p. 218), the J test can be viewed as a specification test to examine whether the model
restrictions are valid. To interpret the rejection of the J test as evidence for the endogeneity of the
instruments, the underlying assumptions must hold with confidence. In addition, the finite-sample
property of the test shows that it is likely to overrejcet the null hypothesis of no endogeneity of
the instruments. In the small sample of my dataset, the J test could indicate correlation between
the instruments and an error term even in the absence of the endogeneity problem. Thus, theoveridentification test could imply a room for improving the specification in explaining thepattern of U.S. multinational production.

5.3 Sensitivity Analysis
Evidence in favor of vertical FDI has been provided with the descriptive statistics andregression results for the Japanese sample, but not for the U.S. While the major concern of theendogeneity of SKILL is already addressed by the IV estimation, the previous regressions could
be sensitive to the empirical specification that is closely based on the knowledge-capital model. I
introduce some alterations in the specification for robustness checks.
First, the SKILL variable is defined in several ways for the model. Specifically, the
SKILL variable measured by the average years of schooling is defined as the natural logarithm tomitigate possible outlier effects of top and bottom countries in educational attainment. The
bottom countries such as Indonesia, India, and Brazil had the average 4 years of education in mysample. On the other hand, the duration of education was around 12 years for the top countries
such as the U.S., New Zealand, and Canada. Table 4 reports the OLS and IV regressions for themodified specification. The columns (1) and (2) show the significantly negative estimates for thelog of skill endowments in the case of Japan while the columns (7) and (8) give the insignificant
coefficients in the case of the U.S. Thus, the results support the conclusion previously made.
25

[Table 4 around here]
Next, it was controversial in prior work whether differences in relative skill
endowments across countries should be defined as the absolute value (Blonigen et al, 2003). To
check the issue, the SKILL variable is defined as the absolute difference in the average years ofschooling between parent and host countries. Although there is little variation in parent-country
relative skill endowments, the difference variable can serve to explore the implication that vertical
FDI should be important when countries become more different in relative endowments. In theJapanese sample, the columns (3) and (4) present the significantly positive coefficients for theabsolute skill difference. However, the columns (9) and (10) do not produce any significant
coefficients for the U.S. sample. The findings imply that cross-country differences in relativeskilled-labor abundance have a positive impact on affiliate sales by Japanese MNEs, but noeffects on U.S. affiliate sales. While previous work on the knowledge-capital model focused on
the specification of skill differences in resolving weak evidence for vertical FDI (Blonigen et al.
2003; Carr et al. 2003), my findings indicate no prominent role of the absolute difference
specification in the results. It is the data source that determines support for vertical FDI.
Finally, skill endowments are measured by the percentage of college graduates in the
population taken from Barro and Lee (2000). I exploit differences in the proportion of primaryand secondary-school graduates in the previous 10 years as the instruments for the college
graduates. In the case of Japanese MNEs, the OLS result in column (5) shows that thecollege-graduates variable has the insignificant coefficient. However, the IV regression provides
the significantly negative coefficient, possibly indicating that the endogeneity of thecollege-graduates variable has a strong upward bias in the OLS estimate. Consistent with theprevious results, Japanese affiliate sales are smaller in the host countries with the greater share ofhighly educated workers in the labor force. In the case of the U.S. sample, columns (11) and (12)do not give any significant results. Therefore, my findings suggest that evidence for vertical FDI
26

is robust to the variable definition.
In addition to the sensitivity to the variable definition of SKILL, there is also the concernthat the schooling instruments used in my analysis could have an effect on MNE activity throughomitted variables, other than current skill endowments. To some extent, the concern is mitigatedby the absence of evidence by J statistic for a correlation between the independent variables andthe error term in the case of Japanese MNEs. Nevertheless, the failure to find evidence does notnecessarily ensure that there are no other transmission channels through which past schoolingcharacteristics could affect current MNE production.
It is useful to assess the validity of IV regressions to the endogeneity resulting frompotential omitted-variables bias. To this end, I largely expand the specification with the following
variables. First, data on the average corporate tax rates are taken from the University of Michigan
World Tax Database to account for the tax effects on the location of multinational production. The
database reports statutory corporate income tax rates that measure maximum marginal tax rates
faced by companies in each country.17 Second, there may be regional effects on the location of
MNE production, which could be correlated with the past schooling characteristics. I exploit datafrom the World Trade Organization to construct an indicator for 3 regional trade agreements: EU,
ASEAN Free Trade Area (AFTA), and Mercosur.18 Lastly, I control for the geographic contiguity
and common language, which are specific to the U.S. sample. The data on common language
come from the International Trade Data website of Raymond Robertson.
Table 5 presents the OLS and IV results for the largely expanded specification withJapanese and U.S. data on affiliate sales. In the case of Japanese MNEs, column (1) shows that
the OLS estimate of the coefficient of SKILL is significantly negative with the larger absolutemagnitude as compared to the OLS estimate obtained from the original specification. Since AFTA
17

Available at http://www.bus.umich.edu/OTPR/otpr/introduction.htm
The European Union (EU) was formed when the Maastricht Treaty was signed in February 1992
and entered into force in November 1993. The ASEAN Free Trade Area (AFTA) was signed in
January 1992 and came into force in January 1993. The Common Market of the South (Mercosur)began when the Treaty of Asunción was signed in March 1991.

18

27

has the significantly positive coefficient among the additional control variables, the previous OLS
regression might have assigned the effects of ASEAN FTA to those of skill endowments on
affiliate sales. The IV regression in column (3) also shows an increase in the absolute size of thecoefficient of SKILL. On the other hand, columns (2) and (4) indicate that skill endowments haveno significant effect on U.S. affiliate sales, even after accounting for additional control variables
that could give rise to an upward bias in the coefficients of SKILL.
[Table 5 around here]
A possible explanation for the upward endogeneity bias is that the past improvement ineducational attainment at the primary- and secondary-school levels has generally a beneficial
effect on economic growth, which strengthens an incentive for further institutional changes toincrease economic gains. Reforms in economic institutions such as administrative procedures,investment rules, and regulatory frameworks could have a positive effect on multinational activity
through a reduction in business costs. If the positive effects of institutional upgrading throughpast developments in the educational attainment are excluded from the IV specification, they
could enter the negative effects of the current skill endowments on Japanese MNE activity, giving
rise to an upward pressure on the estimates of ceteris paribus effects of SKILL. These arguments
imply that the regression analysis tends to downplay the role of host country’s unskilled labor on
multinational production because the better schooling characteristics in the past period can belikely to contribute to preferable, rather than deteriorating, investment environments for current
MNE activity.

6. Conclusion
A recent increase in FDI flows is commonly viewed as arising from verticalfragmentation of a firm’s production process to take advantage of factor-cost differentials acrosscountries. General equilibrium approach to vertical FDI predicts that vertical MNEs should locate
28

unskilled-labor-intensive production in unskilled-labor-abundant countries. Contrary to thetheoretical insight, formal evidence for vertical FDI was surprisingly mixed. This paper
reconsiders the factor-proportions explanation by using panel data on sales of foreign affiliates byJapanese and U.S. multinationals for the years 1990, 1995, and 2000. Robust to a wide variety ofsensitivity checks and endogeneity bias, I find that Japanese affiliate sales are larger in relatively
unskilled-labor-abundant countries. One of the conservative estimates predicts that Japaneseaffiliate sales increase by about 25% when the average years of schooling of the host-country
labor force decrease by one year. On the other hand, there is no evidence that host-country skill
endowments influence U.S. affiliate sales. Thus, my analysis provides strong evidence forfactor-seeking FDI in the case of Japanese MNEs, but not U.S. MNEs.
The empirical results on the linkage between relative skill endowments andmultinational production emerge after carefully controlling for affiliate-data consistency, a varietyof host-country characteristics, and endogeneity bias. A distinctive pattern of Japanese and U.S.
multinational sales is a crucial source in driving the opposite support for vertical FDI. Since
previous empirical work in favor of horizontal FDI tends to focus on U.S. affiliate data, myanalysis empirically demonstrate that the data source on multinational activity may play a largerole in explaining weak evidence for vertical FDI in the literature. In this sense, my work
highlights the importance of an international comparison on the determinants of multinational
activity. Additionally, my findings raise a question of why vertical FDI is stronger for Japanese
MNEs than U.S. MNEs. While a large number of comparative studies on Japanese and U.S. firms
exist, this paper’s findings call for further comparative research in the context of vertical FDI
activity.

29

Table 1. Summary Statistics
Variables
ASALE
SKILL
PSCHOOLSSCHOOL
GDP
MKP
DIST
TC
IC

No. of observations
Japan
U.S.
110
110
110
110
110
110
110
110
110

98
98
98
98
98
98
98
98
98

Mean
Japan
U.S.

Std. Dev.
Japan
U.S.

Min
Japan
U.S.

Max
Japan
U.S.

7.90
7.99
4.52
2.20
5.44
1.86
8.96
31.4
23.1

2.14
2.24
1.40
1.24
1.13
0.66
0.58
12.1
15.5

1.32
3.30
1.92
0.45
3.65
0.61
7.05
10.0
2.17

12.3
12.2
7.66
5.09
9.19
3.32
9.82
64.4
61.5

9.50
7.85
4.40
2.14
5.53
1.83
8.97
32.7
23.0

1.40
2.14
1.30
1.15
1.08
0.67
0.61
12.5
15.6

6.45
3.30
1.92
0.45
3.78
0.61
6.60
10.0
2.17

12.2
11.5
7.66
5.08
8.47
3.32
9.70
64.8
61.5

Table 2. OLS Regression for Determinants of Japanese and U.S. Multinational Activity
Dependent Variable: Log of Real Sales by Manufacturing Foreign Affiliates
Japanese
U.S.
Coefficient
SampleSampleDifference
(1)
(2)
(3)
0.013
-0.297**
Skill Endowments-0.284***(0.084)(0.061)(0.103)Log of GDP
1.097***
0.899***
0.198(0.127)(0.099)(0.161)
Log of Market Potential-1.102***-0.121-0.981**(0.247)(0.170)(0.301)
Log of Distance-1.370***-0.462***-0.908***(0.207)(0.125)(0.242)
Trade Cost
-0.020-0.022**0.002(0.017)(0.008)(0.019)Investment Cost
-0.037*-0.013-0.024(0.014)(0.011)(0.018)Year 1995 Dummy-0.2150.153-0.368(0.372)(0.223)(0.434)
Year 2000 Dummy
0.344
0.216
0.128
(0.386)(0.261)(0.467)
No. of Observations
110
98
208
R2
0.525
0.667
0.635
Note: Heteroskedasticity-consistent standard errors are in parentheses, with ***, **, and * indicating the 1,
5, and 10 percent significance levels, respectively. Column (3) shows OLS estimates of interaction terms
between regressors and a dummy variable for Japanese MNE in the specification including the interactions
and Japanese MNE dummy for pooled sample. A constant term is not reported.

30

Table 3. IV Regression for Determinants of Japanese and U.S. Multinational Activity
Dependent Variable: Log of Real Sales by Manufacturing Foreign Affiliates
Japanese Sample
U.S. Sample
2nd stage
1st stage
2nd stage
1st stage
(1)
(2)
(3)
(4)
-0.035Skill Endowments-0.299***(0.082)(0.064)Log of GDP
1.099***
0.032
0.889***-0.108(0.122)(0.062)(0.095)(0.068)Log of Market Potential-1.104***-0.297**-0.148-0.413***(0.237)(0.105)(0.164)(0.101)
Log of Distance-1.372***-0.284*-0.498***-0.190(0.197)(0.121)(0.126)(0.115)Trade Cost
-0.020-0.009-0.022**0.001(0.016)(0.008)(0.008)(0.007)
Investment Cost
-0.038**-0.010-0.019-0.022**(0.014)(0.007)(0.011)(0.007)
Year 1995 Dummy-0.214
0.191
0.140
0.161
(0.356)(0.152)(0.212)(0.167)
Year 2000 Dummy
0.351
0.131
0.270
0.311
(0.375)(0.160)(0.257)(0.163)
Primary School (t-10)
0.947***
0.923***(0.042)(0.053)
Secondary School (t-10)0.901***
0.885***(0.068)(0.078)
No. of Observations
110
110
98
98
R2
0.931
0.924
0.886
0.846
Partial R2
F statistics for
432.5
228.5
IV Relevance Test
(0.000)(0.000)Hansen’s J statistics for
2.004
6.199
Overidentification Test
(0.157)(0.013)
Note: Heteroskedasticity-consistent standard errors are in parentheses, with ***, **, and * indicating the 1,
5, and 10 percent significance levels, respectively. A constant term is not reported. The null hypothesis for
F test is that the instruments jointly have zero coefficients. The null for Hansen’s J statistics is that the
instruments are uncorrelated with an error term. P-values are in parentheses for these statistics.

31

Table 4. Sensitivity to Alternative Variable Definitions
Dependent Variable: Log of Real Sales by Manufacturing Foreign Affiliates
Japanese Sample
Estimation
OLS
IV
OLS
IV
OLS
IV
(1)
(2)
(3)
(4)
(5)
(6)
Log of Skill-1.94**-2.16***
Endowment(0.60)(0.61)
Absolute Skill
0.36**
0.48***
Difference(0.12)(0.14)
College-0.04-0.51**
Graduates(0.03)(0.19)
Observations
110
110
110
110
110
110
2

R
F statistics
Hansen’s J
statistics

0.52

0.51
232
(0.00)
2.43(0.11)

0.47

OLS
(7)
0.38
(0.43)

IV
(8)
-0.22
(0.46)-0.01(0.06)

98

98

0.67

47.9
(0.00)
3.29(0.06)

5.52(0.00)
2.04(0.15)

U.S. Sample
OLS
IV
(9)
(10)

98

IV
(12)

0.02
(0.03)
98-0.29(0.18)
98

0.03(0.06)

98

0.66
122
(0.00)
6.44(0.01)

OLS
(11)

0.67
229
(0.00)
6.19(0.01)

1.96(0.14)
0.03(0.85)

Note: Heteroskedasticity-consistent standard errors are in parentheses, with ***, **, and * indicating the 1, 5, and 10 percent significance levels, respectively.
GDP, MKP, DIST, TC, IC, year dummies, and a constant term are included, but not reported. The null hypothesis for F test is that the instruments jointly havezero coefficients. The null hypothesis for Hansen J statistics is that the instruments are uncorrelated with an error term. P-values are in parentheses for thesestatistics. College graduates are measured by the percentage of higher school completion in the total population, with the instruments of the percentage ofprimary and secondary school completion in the previous 10 years.

32

Table 5. Sensitivity to Additional Control Variables
Dependent Variable: Log of Real Sales by Manufacturing Foreign Affiliates
Japanese
U.S.
Japanese
SampleSampleSampleEstimation
OLS
OLS
IV
(1)
(2)
(3)
-0.037-0.319***Skill Endowment-0.307***(0.083)(0.080)(0.077)Log of GDP
1.260***
1.018***
1.262***(0.146)(0.131)(0.136)
Log of Market Potential-0.596*0.254-0.591*(0.283)(0.225)(0.264)Log of Distance-1.074***-0.234-1.078***(0.230)(0.325)(0.213)
Trade Cost
-0.044*-0.032**-0.044*(0.019)(0.011)(0.017)
Investment Cost
-0.042**-0.017-0.043**(0.015)(0.014)(0.013)
Year 1995 Dummy-0.413-0.155-0.402(0.445)(0.256)(0.411)
Year 2000 Dummy-0.148-0.147-0.133(0.413)(0.281)(0.383)
Corporate Tax Rate
-0.0230.004-0.023(0.021)(0.016)(0.020)ASEAN Free Trade Area
2.194***
1.307**
2.180***(0.398)(0.384)(0.370)
Mercosur
0.170
0.758
0.172
(0.485)(0.470)(0.446)
EU Single Market-1.203*-0.221-1.231*(0.511)(0.380)(0.479)Geographic Contiguity
0.563(0.658)
Common Language
0.397(0.261)
Observations
94
83
94
R2
0.661
0.725
F statistics for
496.2
IV Relevance Test
(0.000)Hansen’s J statistics for
1.151
Overidentification Test
(0.283)U.S.
SampleIV(4)-0.073(0.073)1.015***(0.117)0.276(0.208)-0.226(0.294)-0.032**(0.010)-0.021(0.012)-0.143(0.235)-0.098(0.260)0.004(0.015)1.282***(0.359)0.795(0.419)-0.287(0.347)0.592(0.588)0.438(0.246)83
283.0(0.000)3.849(0.049)Note: Heteroskedasticity-consistent standard errors are in parentheses, with ***, **, and * indicating the 1,
5, and 10 percent significance levels, respectively. A constant term is not reported. The null hypothesis for
F test is that the instruments jointly have zero coefficients. The null hypothesis for Hansen J statistics is thatthe instruments are uncorrelated with an error term. P-values are in parentheses for these statistics.

33

Figure 1. Pattern of Japanese and U.S. Multinational Sales

2

4

Log of ASALE
6
8
10

12

By Year and Home Country

1990

1995

2000

1990

1995

Japan

2000

U.S.

Source: RIETI and BEA

Figure 2. Affiliate Sales and Relative Skill Endowments for Year 1990
By Home Country
Japan

U.S.

Log of Asale/GDP

0
SGP
MYS
THA

-2

TWN

IDN

-4

BRA
IND PRT

-6

TUR

ESP
MEX
ITA

SGP

HKG
KOR

BRA
AUS

NZL
BEL
NLD
CAN
GBR
USA
IRL
FRA
DEU CHE
GRC
AUT

TUR
IND
IDN

DNK
NOR

HUN

-8

MYS
MEX
ESP
THA ITA

IRL
CAN
BEL
NLD
GBR AUSFRA HKGDEU
TWN
SWE
KORCHE NZLJPNAUTDNKNOR
FIN

SWE

-10
4

6

8

10

12

4

6

Average Years of Schooling
Asale

Fitted values

Source: RIETI, BEA, and Barro and Lee(2000)
Note: Asale and GDP are measured in billions of U.S. dollars.

34

8

10

12

Figure 3. Affiliate Sales and Relative Skill Endowments for Year 1995
By Home Country
Japan

U.S.

0

Log of Asale/GDP

-2
-4
-6
-8

MYS
SGP

SGP
CAN
MYS BELIRLNLD
PHL
IDN
PHL
BRA
GBR AUS
FRA
HKG
THA
COL
TWN
HKG
DEU
MEX ESP CHL
COLVEN
BEL NLD KOR NZLITATWNZAF ISR KOR
CHE
USA
PRT
BRA
AUS
CHL
JPN
ARG
CHN
GBR
TUR
CAN
IND
IDN
FRA IRL
IND
CHN
VEN
CHE
FIN
ESP
PRT
HUN DEUGRC
TUR MEX
ITA
ARG
DNK
SWE
AUT
FIN
ZAF
THA

ISR

-10

POL

4

6

8

10

12

4

6

8

10

12

Average Years of Schooling
Asale

Fitted values

Source: RIETI, BEA, and Barro and Lee(2000)
Note: Asale and GDP are measured in billions of U.S. dollars.

Figure 4. Affiliate Sales and Relative Skill Endowments for Year 2000
By Home Country
Japan

U.S.

Log of Asale/GDP

0
-2
-4
-6

MYS
THA PHL SGP
IDN
HKG
TWN
BEL NLDAUS USA
CHN
CHL
KOR
CAN
MEX
HUN GBR
BRAIND
ZAF
NZL
VEN
DEU
PRT
IRL
CHE
ESP
TUR COLFRAITA GRC
POL
SWE
FIN
ARG

MYS

SGP IRLCAN
BELGBR
PHL
NLD
THA
BRA
DEU AUS SWE
ZAF
CHL
ESP
HKG CHETWN ISRVEN
KORPOLNZLITA FRATUR COLCHN
ARG AUT
IDN
FIN
JPN
IND
MEX

DNK

-8

AUT

-10
4

6

8

10

12

4

6

Average Years of Schooling
Asale

Fitted values

Source: RIETI, BEA, and Barro and Lee(2000)
Note: Asale and GDP are measured in billions of U.S. dollars.

35

8

10

12

Appendix
Table A1: Variable Definition and Data Source
Variable
Definition
ASALE
Log of aggregate sales of all manufacturing
affiliates in each country measured in year
2000 U.S. dollars, using IFS data on a U.S.
wholesale price index and the period
1989-2002 average of yen/dollar exchange
rates
SKILL
Average years of schooling of people overage 25PSCHOOL
Average years of primary schooling ofpeople over age 25 in the previous 10 years
SSCHOOL
Average years of secondary schooling ofpeople over age 25 in the previous 10 years
GDP
Log of real GDP in billions of year 2000
U.S. dollars
MKP
Log of sum of distance-weighted GDP
levels of all markets excluding host GDP
DIST
Log of distance in kilometers between
capital cities in home and host countries
TC
Ordinal index of protectionism, ranging
from 0 to 100
IC
Ordinal index of overall country risk,
ranging from 0 to 100; overall risk scoreconsists of 9 weighted individual scores
including political risk (25%), economic
performance (25%), debt indicators (10%),debt in default or rescheduled (10%), credit
ratings (10%), access to bank finance (5%),
access to short-term finance (5%), access tocapital markets (5%), and discount on
forfaiting (5%)

36

SourceJapanese affiliate data fromthe Research Institute of
Economy, Trade and Industry;
U.S. affiliate data from Bureau
of Economic Analysis, U.S.
Department of Commerce

Barro and Lee (2000)

World Development Indicator
Raymond Robertson Website
World Competitiveness
Yearbook

Euromoney

Table A2: Country List and CodeCountry
CodeSampleCountry
CodeSampleArgentina
ARG(JP, US)Japan
JPN( , US)
Australia
AUS(JP, US)
Malaysia
MYS(JP, US)
Austria
AUT(JP, US)
MexicoMEX(JP, US)
Belgium
BEL(JP, US)
Netherlands
NLD(JP, US)
Brazil
BRA(JP, US)New Zealand
NZL(JP, US)
CanadaCAN(JP, US)
NorwayNOR(JP, US)
Chile
CHL(JP, US)
Philippines
PHL(JP, US)
China
CHN(JP, US)
PolandPOL(JP, US)
Colombia
COL(JP, US)
Portugal
PRT(JP, US)
Denmark
DNK(JP, US)Singapore
SGP(JP, US)
Finland
FIN(JP, US)South Africa
ZAF(JP, US)France
FRA(JP, US)South Korea
KOR(JP, US)
Germany
DEU(JP, US)
Spain
ESP(JP, US)GreeceGRC(JP,)
SwedenSWE(JP, US)
Hong Kong
HKG(JP, US)
Switzerland
CHE(JP, US)
Hungary
HUN(JP, )
TaiwanTWN(JP, US)
India
IND(JP, US)
Thailand
THA(JP, US)
Indonesia
IDN(JP, US)
TurkeyTUR(JP, US)
Ireland
IRL(JP, US)
United Kingdom
GBR(JP, US)
IsraelISR(JP, US)
United States
USA
(JP,
)
Italy
ITA
(JP, US)
Venezuela
VEN(JP, US)
Note: JP and US indicate that Japanese and US samples have a country for at least one year,
respectively.

37

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39