Discussion Paper Series No.166
Cost Heterogeneity and the Destination of Foreign
Direct Investment
Seiichi Katayama

Kobe University

Sajal Lahiri

Southern Illinois University

Eiichi Tomiura

Kobe University

January

2005

Discussion papers are a series of manuscripts in their draft form.
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January 25, 2005

Cost Heterogeneity and the Destination of Foreign
Direct Investment
By
Seiichi Katayama,§ Sajal Lahiri ‡ and Eiichi Tomiura §§Research Institute of Economics and Business Administration, Kobe University, Rokkodai,
Nada-ku, Kobe 657-8501, Japan.
‡
Department of Economics, Southern Illinois University, Carbondale, IL. 62901-4515, U.S.A.
Corresponding author: Sajal Lahiri, Department of Economics, Southern Illinois University,
Carbondale, IL. 62901-4515, U.S.A., E-mail: lahiri@siu.edu, FAX: +1-618-453-2717

Cost Heterogeneity and the Destination of Foreign
Direct Investment

ABSTRACTThis paper first of all develops a theoretical model to examine a number of heterogeneousfirms’ choice between making export-oriented foreign direct investments (FDI) in a hostcountry and making FDI in another country to serve the market there. It is shown that all
firms below a critical level of efficiency invest in the first country, and the other relatively
more efficient firms invest in the second host country. The hypothesis is tested using firmlevel data on 118,300 Japanese firms covering the entire manufacturing sector. Multinomial
logit estimates strongly support our theoretical findings.
JEL Classifications: F2, H2
Keywords: Cost heterogeneity, oligopoly, foreign direct investment, export-oriented FDI

1Introduction

One of the consequences of globalization is an increased competitiveness in the world economy. Producers are having to find ways to serve the global marketplace in the most efficientpossible way. Foreign direct investment (FDI) as a means to reach such a marketplace has
been rapidly increasing in popularity. According to UNCTAD, the ratio of inward plus outward foreign direct capital to global gross domestic product is 21%. Rather than controlling
inward FDI — which was the order of the 1960s and 70s — more and more countries aretrying to attract FDI by creating favorable conditions. During the 1990s, 94% of FDI-related
regulations were removed in both developed and developing countries (see UNCTAD (1998)).
The importance of FDI in today’s world economy cannot be overemphasized. One
reason for FDI is the proximity to consumers. However, this is not the only reason. For
example, according to UNCTAD (1998), foreign-affiliate exports now make up about onethird of total world exports. Thus export-oriented FDI has also been increasing in currency.
Furthermore, FDI can also take the form of either greenfield investment or cross-borderacquisitions.
Because of its enormous importance in global economic activity, FDI has received
a great deal of attention from academic economists, and the literature is vast. There are
two broad strands in the theoretical literature. The first strand examines the incentives offoreign firms to take part in FDI and their choice among various alternative modes (including
direct exports) to serve the intended markets. Brander and Spencer (1987), Ethier (1986),
Helpman (1984), Horstmann and Markusen (1992), and Motta (1992) are some of the early
papers that belong to this aspect of the literature. The second strand examines competition
among host countries for FDI through public policies and analyzes the effects of FDI on thewelfare of the host country. Grossman (1984), Haufler and Wooton (1999), Itagaki (1979),
Janeba (1995), Lahiri and Ono (1998), and Tsai (1999) are some of the contributions to thispart of the literature.
1

A growing body of recent literature acknowledges the fact that foreign firms are nothomogeneous and examines to what extent firm heterogeneity can explain the choice ofdifferent modes of reaching the global marketplace.1 Nocke and Yeaple (2004 and 2004a)
consider the choice between cross-border acquisitions and greenfield FDI. In Helpman et al.
(2004) the choice is between greenfield FDI and exports. Grossman and Helpman (2003)
and Antras and Helpman (2004) consider the choice between foreign outsourcing and FDI.
This paper complements this new literature by considering the choice among heterogeneous firms between export-oriented FDI and FDI to serve the market in the host country.
This distinction is important as, for example, about a third of Japanese FDI in Asia areexport-oriented. We first of all develop a theoretical oligopolistic model with a number offirms who differ in their efficiency levels. Each of the firms has a choice of either making
FDI in one host country and export all its output to its home country or investing in asecond host country and sell its output in the host country. We characterize an equilibrium
where one set of firms make export-oriented FDI and remaining firms invest in the second
country. In the theoretical part we develop a number of hypotheses which are then tested,using multinomial logit analysis, for firm-level data from 118,300 Japanese firms covering
the entire manufacturing sector there.
Empirical research on FDI has been severely constrained by the lack of availabilityof firm-level data. In the absence of such data, some of the early studies on FDI focused on
host-country factors at aggregate levels (see, for example, Kravis and Lipsey (1982), Wheeler
and Mody (1992), and Brainard (1997)). There is now a few micro data sets, and a newliterature is growing side-by-side with the theoretical literature on FDI by heterogeneousfirms. Head and Ries (2003) found that the Japanese firms investing in low-income countries seem weakly less productive than the firms investing in high-income countries. Theirrelatively small sample size of 1070 only publicly-listed firms does not properly represent the1

The wider literature on oligopolistic industry with heterogeneous firms is not voluminous either. An
early work is Lahiri and Ono (1988). See Lahiri and Ono (2004) for more recent literature.

2

Japanese manufacturing sector. In the firm-country-year panel study for US FDI by Riker
and Brainard (1997), the efficiency levels of firms is not considered at all. Helpman et al.
(2004) relate intra-industry dispersion of efficiency levels with US firms’ choice between FDI
and exports. Nocke and Yeaple (2004 and 2004a) examine the role of efficiency levels among
US firms in their choice between cross-border acquisitions and greenfield FDI. Finally, using
the same data set as this paper, Tomiura (2004) examines Japanese firms’ choice between
outsourcing, FDI and exports.
The layout of the paper is as follows. The following section develops the theoreticalframework. Section 3 carries out the econometric analysis, and some concluding remarks are
made in section 4.

2

A theoretical analysis

There are N firms belonging to a country (denoted by country c) with constant marginal(average variable) costs ci , i = 1, · · · N . These firms locate in one of two possible hostcountries. FDI in one of the host countries — called country a — is purely export oriented
in the sense that outputs by the foreign firms are exported back to country c.2 We assume
that country a has unemployment. The other host country — called country b — receives
FDI to serve its own market. That is, outputs by foreign firms in country b are solely soldin country b. We shall call this country the consuming country and assume that there is no
unemployment in this country. The firms located in countries a and b produce two different
goods and compete in the Cournot oligopolistic markets in countries c and b respectively.
We shall establish an endogenous distribution of the firms in the two host countries,
and this sorting equilibrium will be found by equating the profits of a marginal firm in thetwo countries. We consider a three-stage game. In stage 1, the firms make their location
decisions. In stage two, the governments decide on their policy levels, and in the final stage
2

Sometimes we shall call the host country where export-oriented FDI is made the export-oriented country.

3the firms compete in the output markets in Cournot oligopolistic manners. We work withbackward induction in order to achieve a sub-game-perfect equilibrium.
Without loss of generality suppose that firms 1, · · · n are located in country a and firms
n, · · · , N are located in country b. Since the marginal firm, i.e., the nth firm, is indifferent
between locating in the two countries, for characterizing the equilibrium we assume that thisfirm is located in both countries.
Total demand of goods in the two countries are Db and Dc . Denoting the output offirm i while operating in country j by xji , we have:
N
X

Db =

xbi ,

(1)

xai .

(2)

i=n
n
X

Dc =

i=1

Inverse demand functions in the two countries are:pc = αc − βc Dc ,(3)

pb = αb − βb Db .

(4)

Profits of firms in the two countries are:πia (n) = (pc − ci + sa )xai , i = 1, · · · n,(5)

πjb (n) = (pb − cj + sb )xbj , j = n, · · · N,

(6)

where sa is output subsidy in country a and sb is output subsidy in country b. The argumentn in the notation for profits indicate the allocation of foreign firms between the two countries,
i.e., firms 1, · · · , n in country a and firms n, · · · , N in country b.
Assuming Cournot conjectures, first order profit-maximizing conditions in the two4countries are:pc − ci + sa = βc xai , i = 1, · · · n,(7)pb − cj + sb = βb xbj , j = n, · · · N.

(8)

Solving (7) and (8), we get
Dc =
xai =
Db =
xbj =

P
n(αc + sa ) − ni=1 ci,
βc (n + 1)P
αc + sa + nj=1 cj − (n + 1)ci
, i = 1, · · · n,
βc (n + 1)
P
(N − n + 1)(αb + sb ) − N
i=n ci,βb (N − n + 2)P
αb + sb + N
i=n ci − (N − n + 2)cj
. j = n, · · · N.
βb (N − n + 2)

(9)
(10)
(11)
(12)

We make the assumption that either market can support any number of the N firms.
A sufficient condition that guarantees this is:
Assumption 1

min (αc , αb ) > N ci , i = 1, · · · N .

From equations (10) and (12) it follows that, for given levels of sa and sb , we havexai ≤ xaj ⇐⇒ ci ≥ cj , i, j = 1, · · · n,(13)

xbi ≤ xbj ⇐⇒ ci ≥ cj , i, j = n, · · · N,

(14)

That is, as one would expect, in each market a firm with a higher cost level produces a lower
level of output.
Welfare in the two countries are
Wa =

n
X

ci xia − sa

i=1

n
X

xai ,

(15)

i=1

Wb = CS − sb

N
X
i=n

5

xbi ,

(16)

where consumers’ surplus in country b satisfies
dCS = −Db dpb ,(17)

The first term in (15) is the wage income generated in country a by foreign firms,3 and thesecond term is the subsidy payments to the foreign firms which are financed by lump-sum
taxation. For country b, there is no wage income as there is n unemployment in that country,
but instead the first term is the consumers’ surplus.
The two host countries decides optimally the subsidy levels, and the first-order welfaremaximizing conditions are:
n
n
n
X
X
dWa
dxai X a
dxai
=
ci
−
xi − sa
= 0,
dsa
dsa
dsa
i=1
i=1
i=1

(18)

N
N
X
dxbi
dWb
dpb X b= −Db ·−
x − sb= 0,
dsb
dsb i=n i
dsb
i=n

(19)

where from (10) and (12), we havedxai
1=
, i = 1, · · · n,dsa
βc (n + 1)

(20)

dxbi
1
=
, i = n, · · · N,dsb
βb (N − n + 2)

(21)

Therefore, using (10), (12), (20) and (21), from (18) and (19) we get the optimallevels of subsidies as
ŝa =
ŝb

2

Pn

i=1 ci − nαc

2n

Pn
=

i=1 cin1− αc ,
2PPN−αb (N − n + 1) + N
i=n cii=n (ci − αb )==.
(N − n + 1)(N − n + 3)
(N − n + 1)(N − n + 3)

(22)
(23)

From assumption 1 and equation (23), it immediately follows that ŝb < 0, i.e., theconsuming country taxes the foreign firms. This is an extension (to the case of multiple
3

Implicitly, we assume that labor is the only factor of production in the oligopolistic sector.

6

heterogeneous foreign firms) of a result due to Katrak (1976) where it is shown that the
optimal policy for a host country toward a foreign monopolist is to tax it. In view ofassumption 1, ŝa is also negative. Moreover, it can be verified that, controlling for thenumber of firms in the two countries, ŝb < ŝa . That is, the optimal tax is lower in country
a than in country b. The reason for this is the presence of unemployment in country a: thehigher are the marginal costs, the greater is employment created. Thus, less less efficientfirms in country a receive higher subsidy (pay lower tax) than the more efficient firms incountry b.
Substituting (22) into (10) and (23) into (12), we get(n1X
cj − ci
n j=1

)

xai

1
αc
+
·
=
2βc (n + 1) βcxbj

α b − cj
N −n+2=+·βb (N − n + 3) βb (N − n + 3)

,
(

(24)
N
X
1
ci − cj
N − n + 1 i=n

)
,

(25)

From (24) and (25), it follows thatxai ≤ xaj ⇐⇒ ci ≥ cj , i, j = 1, · · · n,

(13a)xbi ≤ xbj ⇐⇒ ci ≥ cj , i, j = n, · · · N,

(14b)

That is, the qualitative results in (13) and (14) do not change after the substitution of the
optimal values of the subsidies in the expressions for equilibrium output levels.
We shall now prove a lemma which shall useful in deriving our main result.

Lemma 1 Suppose ci = ci+1 + δ, i = 1, · · · N − 1. Then, πna (n) is a decreasing, and πnb (n)an increasing, function of n.

Intuitively, an increase in n increases the number of firms in country a and reduces
that in country b. This, ceteris paribus, would decrease the profits of the marginal firm in7

country a and increase that in country b. However, given the cost structure, an increase in nwould decrease the average of the marginal costs and the marginal cost of the marginal firms
in both countries. This will increase the profits of the marginal firms in both countries. The
net effect is that the profits of the marginal firm in country a increases, and that in countryb decreases, as n increases.
We are now in a position to state and prove the main theoretical result of the paper.
We shall need the following assumption which states that a firms makes a higher profit in acountry if it is the only firm there as compared to the case where it exists with all the otherfirms in the other country.
Assumption 2

π1a (1) > π1b (1)

and

b
a
πN
(N ) < πN(N ).

Proposition 1 Suppose that the marginal costs increase by a constant increment δ. Then
there exists a unique n such that all firms with marginal costs more than or equal to cn locate
themselves in country a and the rest locate in country b.
Proof: Without loss of any generality assume that c1 > c2 > · · · > cN and that ci = ci+1 + δ.
Consider first a situation where firm 1 (the most inefficient firm) is located in country a
and all the firms (including firm 1) are located in country b. From assumption 2 we knowthat firm 1 makes more profit when it is in country a than when it is in country b with all
the other firms. That is, π1a (1) > π1b (1). Next consider the case where firms 1 and 2 arelocated in country a and all other firms (including firm 2) are located in country b. From
Lemma 1, we know that π2a (2) < π1a (1) and π2b (2) > π1b (1). If π2a (2) < π2b (2), the equilibrium
allocation is where only firm 1 locates itself in country a, and the rest in country b. If not,we continue to bring the highest-cost firm from country b to country a until for some n weba(n + 1), and in this case firms firms 1, · · · , n locate in country a(n + 1) < πn+1
have πn+1

and firms n, · · · , N in country b. The existence of a unique n is assured because of Lemma
1 and Assumption 2. The equilibrium is depicted in figure 1: point A is the equilibrium. 28[Figure 1 here]

The above proposition predicts that relatively inefficient firms make export-oriented
FDI, and the more inefficient firms serve the markets in the host countries. One intuitive
reason for the above result is that the export-oriented host country makes it more attractive
for the less efficient firms to invest there as it suffers from unemployment and less efficientfirms, ceteris paribus, create more employment.
We now consider two comparative-static exercises. First, as the distance between two
consecutive marginal costs δ increases, from (A.1)-(A.4) it follows that, for each n, πna (n)increases and πnb (n) decreases. In figure 1, the new equilibrium is given by point B, and it
should be clear that equilibrium value of n increases. Noting that an increase in δ increases
the dispersion of the marginal costs and our model predicts that increased dispersion in
efficiency levels will increase export-oriented FDI and decreases FDI in consuming countries.
An increase in δ makes the firms more attractive for the export-oriented country as they create more employment and less attractive for the consuming country as increased inefficiency
decreases consumers’ surplus. This raises the profit of the marginal firm in country a andreduces that in country b resulting a switch for some firms from country b to a.
Finally, consider an increase in c1 which will shift the distribution of marginal costs
to the right. From (A.1)-(A.4) we find that such an increase will not change πna (n), butwill decrease πnb (n). The equilibrium point will move to point C in figure 1 increasing theequilibrium value of n. This result predicts that a decrease in the average efficiency level
will increase export-oriented FDI.
Having derived a few theoretical predictions about the location of FDI, in the next
section we shall test these hypotheses using firm-level data from Japan.

9

3

An empirical investigation

This section is devoted to an empirical investigation of our theoretical predictions. The
most important testable hypothesis derived from our theoretical model is that relatively lessefficient firms are more likely to make export-oriented FDI. Another prediction is that ahigher dispersion in the efficiency levels results in more export-oriented FDI and less FDI toserve the host markets. We will test these hypotheses directly using firm-level data.

3.1

Description of data

We derive firm-level data from the Basic Survey of Commercial and Manufacturing Structure
and Activity (Sho-Kogyo Jittai Kihon Chosa in Japanese).4 This survey covers 118,300
Japanese manufacturers without any firm-size thresholds in all manufacturing industries,5and contains a range of data for the year 1998, such as sales, the number of employees,
capital, R&D spending, the number of personal computers used in the firm, and industry
classification.6 The number of firms in our sample is much larger than those used by previous
studies on FDI, ensuring that the survey provides an accurate representation of the entire
manufacturing sector in Japan.
The survey captures FDI in terms of the number of foreign subsidiaries/affiliates.
Regarding regional destinations of FDI, Asia is considered separately from the rest of theworld, while no further geographical disaggregation is available in the survey.7 As FDIfrom Japan predominantly go either into US, EU, and Asia, we take Asian countries to beexport-oriented ones and the rest of the world as consuming countries, corresponding to the4
The access to micro-data files was made possible by by Ministry of Public Management, Government ofJapan (Permission No. 428). The micro-data tabulations were done by one of the authors. Any researcher
can have access to the same data set as long as she/he obtains individual official permission from thegovernment in advance.
5
This paper focuses on manufacturing, though commercial sectors are also covered by the survey.
6
The Basic Survey of Business Structure and Activities (Kigyo Katsudo Kihon Chosa in Japanese) also
contain similar data, but only for limited numbers of large firms (defined as those with more than fifty
employees and capital of more than thirty million yen).
7
Foreign affiliates with ownership shares of less than twenty percent are not identified with geographicaldisaggregation.

10

classification in theoretical section. This approximation is consistent with stylised facts thatmany Japanese firms invest in Asia for the export-platform purpose and in US and EU for
the proximity to consumers. For example, the aggregate statistics from the Basic Surveyof Overseas Business Activities (Kaigai Jigyo-katsudo Kihon Chosa, in Japanese) confirm
that more than ninety percent of the output produced by Japanese-owned manufacturing
affiliates located in North America or in Europe are sold within the region, but one-thirdof the output produced by Japanese manufacturing affiliates in Asia are exported to otherregions.8 This contrast justifies our assumption.

3.2

Summary statistics

Some descriptive statistics are summarized in Table 1. We can exploit rich cross-firm variability in our sample, as the standard deviations are much larger than the averages. Amongthe firms that invest abroad, on average, a firm has nine foreign affiliates, six of them being
located in Asia.
Table 2 reports intra-industry dispersions of productivity and the share of exportoriented countries in FDI for each industry, directly calculated from our firm-level data.
The industries are defined at the two-digit level because some of the three-digit industries
include very few firms. Our theoretical model predicts that a higher intra-industry efficiency
dispersion results in more firms investing in export-oriented countries. Descriptive statistics shown in Table 2 clearly supports our prediction. Here, we measure the dispersion interms of the coefficient of variations, which is defined as the standard deviations divided by
the mean. The efficiency is here measured in the labor productivity (sales divided by the
number of regular employees) because no cost data are available at the firm level. Moreinter-firm dispersion in productivity within each industry is associated with higher share of
8

The share of intra-region sales in 2002 (the most recent year currently available) are 94.7% for North
America, 93.3% for Europe, and 66.8% for Asia. This contrast remains stable over the years. Basic Surveyof Overseas Business Activities is the unique data source for intra-firm trade, but its sample size is severely
limited. Our survey has no intra-firm trade data but covers sufficient number of firms to be representativeof the whole manufacturing.

11

firms investing in Asia. For example, the productivity tends to be especially dispersed acrossfirms in export-dependent industries investing heavily in Asia such as textiles, apparels, andelectric machinery. On the other hand, the transport equipment industry is characterized
by relatively low intra-industry productivity dispersion and high propensity to invest for
proximity to consumers. The correlation between these two variables is as high as 0.327
if we exclude the miscellaneous industries for which intra-industry measures cannot be appropriately defined.9 Thus, by using firm-level data for Japan, in line with Helpman et al.
(2004) we can tentatively confirm an important role of intra-industry dispersion in the firm’s
efficiency levels for their FDI decision. As noted before, whereas Helpman et al. (2004) areconcerned with choice between FDI and exports, we analyze the choice between two typesof FDI.
To further examine the productivity effects not summarized by the descriptive data
presented in this subsection, the next subsection directly estimates a multinomial responsemodel formalizing each firm’s choice of FDI destinations.

3.3

Empirical specifications

A firm chooses one of the following three options: (a) investing only or mostly in exportoriented countries, (b) investing only or mostly in consuming countries, or (c) staying in thehome country and therefore not taking part in FDI. Our theoretical model focused only on(a) and (b); Helpman et al. (2004) on the other hand considered (b) and (c). In reality, thechoice often involves all three options. To allow for purely domestic firms, we add the third
option. As a robustness check, we also estimate the binomial Logit model where a firm’s
choice is only between options (a) and (b). This is done for the sub-sample of firms that dotake part in FDI.
9

The correlation remains positive (0.15) even if the miscellaneous industries (34) are included.

12

We estimate the Multinomial Logit model specified as follows.
P (y = j/x) =exp (xβj ),P3
1 + k=1 exp(xβk )(j = 1, 2, 3).

The choice of the firm is denoted by y. To take account that some firms simultaneously
invest in both regions, a firm is defined to invest mostly in consuming countries (exportoriented countries, respectively) when the number of the firm’s foreign affiliates located inconsuming countries is larger (no less) than that in export-oriented countries.
Since we include industry dummies to control for any inter-industry variations, andsince most of the variations in wages are likely to be across industries, we can regard theordering of firms in cost as the same as that in labor productivity by assuming that wage
rates are the same across firms within the same industry.
As for the regressor vector x explaining a firm’s choice y, we use the firm’s laborproductivity Q/L. To check the robustness, we also use three other alternative proxies for
productivity. They are firm size (in sales), domestic market share,10 and ATFP (Approximate
Total Factor Productivity) defined by:11
ATPF = ln

Q 1
K− · ln .
L 3
LTo control for other relevant factors, we also estimate alternative specifications which additionally include capital-labor ratio (physical tangible assets divided by the number of regular
employees), R&D intensity (R&D-sales ratio), the computer-usage intensity (the number of
personal computers used in the firm normalized by the firm size), and the intra-industry
productivity dispersion.12
10

The size of a firm or its share in the home market are good proxies because in most models these variables
are positively related with productivity.
11
For the definition of AFTP, see, for example, Griliches and Mairesse (1990).
12
All the explanatory variables, except dummies, are in logarithm. Before taking logarithm, we add one
to R&D intensity and PC-usage intensity to take care of a large number of firms with zero R&D spending
or no computers.

13

3.4

Estimation results

The estimation results from the multinomial response model are reported in Table 3. Interfirm heteroskedasticity is taken into account in the estimations. The coefficient on productivity is statistically significant at any conventional significance levels. As the response
probability of the choice j relative to the base category (no FDI in the first five cases) is
given by pj /p0 = exp(xβj ), the significantly positive estimate on the productivity indicatesthat more efficient firms are more likely to invest abroad rather than choosing the domestic
option (no FDI).
Furthermore, we find that the productivity coefficient is larger for FDI in consuming
countries than FDI in export-oriented countries in all cases reported in Table 3. As the
log-odds ratio of any two choices is given by log[pj /pk ] = x(βj − βk ), this implies that ahigher productivity of a firm is associated with a firm’s choice of FDI in consuming countries
relative to the choice of FDI in export-oriented countries. Thus, high productivity leads
firms to choose FDI in consuming countries compared not only with the no FDI option but
also with the choice of investing in export-oriented countries.
To get an economic sense of the magnitude of the estimates, we calculate the effectof productivity changes on the relative response probability. As the difference in the productivity coefficient estimate, which is interpreted as the elasticity of odd ratio with respect
to productivity, is estimated at around 0.2. The probability of a firm choosing FDI in consuming countries relative to that in export-oriented countries (Asia) increases from 0.45 to
0.59 when the productivity of a firm rises by one-standard deviation from the mean in our
sample.13 Thus, the impact of productivity on a firm’s destination choice of FDI is quite
sizable.
Our principal finding is not affected by the use of alternative productivity measures,
13
The mean relative probability is calculated from the share of ROW relative to Asia in terms of theaverage number of foreign affiliates. Other figures are also derived from Table 1.

14

as reported in rows (2), (3) and (4) of Table 3. Row (5) of the same table shows that theinclusion of other controls does not affect our results. The estimated sign indicate that theprobability of investing in consuming countries compared with export-oriented countries ishigher when the firm’s capital-labor ratio, R&D intensity, or the computer usage intensity
is higher.
On the effect of intra-industry productivity dispersion on a firm’s choice, we confirm
our theoretical prediction. We use two alternative definitions of dispersion: coefficient ofvariation in row (6) and standard deviation in row (7). As reported in these two rows,
when the inter-firm dispersion within an industry is larger, a firm in the industry invests
in export-oriented/consuming countries with higher/lower probability, ceteris paribus. This
relation is found statistically significant at any conventional significance levels. Even withthis dispersion as an additional right hand side variable, the estimated coefficient on the
productivity remains higher for FDI in consuming countries than FDI in export-oriented
countries. It is also worth noting that in both row (6) and row (7), the coefficient for
dispersion is positive for export-oriented countries and negative for consuming countries.
Thus, whereas a higher dispersion increases the probability of investing in export-oriented
countries relative to investing only at home, it decreases the probability of investing in
consuming countries relative to staying at home. This contrast is interesting as it indicatesthat it is important to distinguish between the two types of FDI we consider here.
In the theoretical section we also predicted that a decrease in average productivity(an increase in c1 ) increases FDI in export-oriented country and decreases that in the consuming country. In order to test this prediction, we include average industry productivity
as one of the regressors in row (7). The result demonstrates that the probability of investing in export-oriented countries increases significantly when the average productivity level
decreases, supporting our theoretical prediction.14
14
It should be noted that average productivity does not have a statistically significant impact on decreasing
the probability of investing in consuming countries, thought the sign is as predicted. The effect for theexport-oriented country is statistically significant.

15

As the final robustness check, we exclude all the firms without FDI and concentrateon the binary choice between options (a) and (b) described above. As reported in the lastrow of the table, our main results remain the same. Consequently, our finding is robust to
the inclusion of a large number of purely domestic firms.

4

Conclusion

In view of the enormous importance of foreign direct investment (FDI) in the highly integrated world economy today, not surprisingly the literature on FDI is voluminous. Manydifferent aspects of it have been examined using many different theoretical frameworks. In
recent years, there have been an recognition that different types of firm heterogeneities canto an extent explain different modes of serving the global market place such as direct exports,
outsourcing, greenfield FDI, cross-border acquisitions etc.
In this paper, we developed a theoretical model where a number of firms which differ
in their efficiency levels, make a choice between export-oriented FDI and FDI for serving
the market in the host country. Thus our model complements the existing literature byextending the set of options for foreign firms. Our theoretical model predict that relatively
less efficient firms are more likely to make export-oriented FDI. To be more specific, we findan equilibrium allocation of firms between the two host countries such that firms at the lower
end of the efficiency distribution make FDI in a host country and export all their outputs
back to their home country, and the firm at the higher end of the efficiency distribution
invest to serve the market in the host country. In the second half of the paper we test
our theoretical prediction empirically, using multinomial logit analysis, for the Japanesemanufacturing sector. We find that our data set strongly support the theoretical predictions
we derived in this paper.

16

Table 1: Summary Statistics
Average Standard Deviation
FDI total
9.387
14.564
FDI in Asia
6.468
7.761
Productivity
18.47
28.29
Firm size
2,629
45,975
Notes: FDI is measured by the number of foreign affiliates with ownership shares no less than
20%. Productivity is labor productivity (sales over the number of regular employees). Firm size isin sales (in million yen). The statistics are calculated only over firms for which there are data.
Table 2: Intra-Industry dispersion and the share ofexport-oriented countries
Intra-industry% Share ofIndustry
Dispersion ofExport-oriented
Productivity Countries in FDI
12. Food manufacturing
0.905
68.9
13. Beverages, Tobacco & Feed
0.704
53.9
14. Textile
1.121
82.5
15. Apparel & Textile products
1.118
92.6
16. Timber &Wooden products
0.685
65.0
17. Furniture & Fixture
0.551
75.5
18. Pulp & Paper products
0.558
61.7
19. Printing & Publishing
0.691
60.9
20. Chemical products
0.647
67.4
21. Petroleum & Coal products
1.009
61.9
22. Plastic products
0.732
91.2
23. Rubber products
0.579
78.9
24. Leather & Fur products
0.729
88.9
25. Ceramic, Stone & Clay products
0.655
75.3
26. Iron & Steel
0.614
75.3
27. Nonferrous Metals
0.688
85.1
28. Metal products
0.604
76.8
29. General Machinery
0.633
63.2
30. Electric Machinery
0.795
77.4
31. Transportation Equipment
0.566
65.3
32. Precision Instruments
0.533
64.7
34. Miscellaneous manufacturing
1.805
70.4
Correlation 0.327
Notes: The first column lists two-digit industries. The second column measures intra-industry
dispersion in terms of the coefficient of variations. The third column is the percentage share offirms with more affiliates in Asia than in other regions. All figures are defined for firms investingoverseas. The miscellaneous industries (34) are excluded from the cross-industry correlation.

17

Table 3: Results from Multinomial Logit model
Model#

Explanatory
variables ↓Productivity

FDI inConsuming
Countries
1.390 (0.031)

FDI inExport-oriented
Countries
1.169 (0.021)

(1)
(2)

Firm size

1.192 (0.021)

0.951 (0.013)(3)

Domestic
Market Share
ATFP

1.158 (0.021)

0.934 (0.013)

0.914 (0.030)

0.802 (0.020)

Productivity
Capital/Labor
R&D/Sales
PC/SalesProductivity
Capital/Labor
R&D/Sales
PC/SalesCoefficient of
Variation
Productivity
Capital/Labor
R&D/Sales
PC/SalesSt. Deviation
Av. Industry
Productivity
Productivity

1.119 (0.038)
0.474 (0.027)
9.830 (1.569)
2.537 (0.337)
1.067 (0.035)
0.402 (0.026)
11.681 (1.739)
2.901 (0.474)

0.925 (0.024)
0.311 (0.017)
8.385 (1.146)
0.568 (1.207)
0.902 (0.023)
0.240 (0.016)
9.974 (1.265)
2.051 (0.505)-0.562 (0.173)
1.091 (0.035)
0.416 (0.026)
11.804 (1.756)
2.940 (0.442)-0.485 (0.169)

0.254 (0.077)
0.936 (0.023)
0.260 (0.016)
10.180 (1.282)
2.046 (0.528)
0.351 (0.076)-0.020 (0.229)
0.241 (0.078)-1.204 (0.143)

(4)

(5)

(6)

(7)

(8)

STATISTICS
Pseudo R2 =0.141# Firms =118,300
Pseudo R2 =0.337# Firms =118,300
Pseudo R2 =0.324# Firms =118,300
Pseudo R2 =0.072# Firms =95,645
Pseudo R2 =0.144# Firms =95,645

Pseudo R2 = 0.109# Firms =95,645

Pseudo R2 =0.111# Firms =95,645

Pseudo R2 =0.082# Firms =3,495

Notes: The base category is no FDI for the first seven cases, while the last row reports the binomial
estimate relative to FDI in export-oriented countries, excluding no-FDI firms. Heteroskedasticityrobust standard errors are in parentheses. Industry dummies are included in all cases except (6)and (7). All the explanatory variables, except dummies, are in logarithm.

18

Figure 1: The Equilibrium Distribution of Firms
pn(n)

b

p n (n)d(d, c1)AB
Cap n (n)n19Appendix: Proof of Lemma 1
When ci = ci+1 − δ, equations (24) and (25) reduce to
xan =
xbn =

αc
1 (n − 1)δ
+·,2βc (n + 1) βc
2αb − cn
N −n+2(N − n)δ
−·,βb (N − n + 3) βb (N − n + 3)
2

(A.1)
(A.2)

From (5), (6), (7) and (8), we get
πna (n) = βc (xan )2 ,³ ´2πnb (n) = βb xbn .

(A.3)
(A.4)

From (A.2) and (A.4) it immediately follows that πnb (n) is an increasing function of n.
From (A.1), it can be shown that xan is a decreasing function of n if αc > (n + 1)2 δ. However, sincecn+2 = c1 − (n + 1)δ > 0, from assumption 1 it follows that αc > (n + 1)2 δ and thus xan (and πna (n))
is indeed a decreasing function of n.
220

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