G-SEC WORKING PAPER No.2
Divestment of Foreign Manufacturing Affiliates:
Country Platforms, Multinational Plant Networks,
and Foreign Investor Agglomeration
René Belderbos * and Jianglei Zou **August, 2005

Abstract
We develop hypotheses concerning the impact of multinational firms’ international plant
networks and host country foreign investor agglomeration on the divestment of manufacturing
affiliates, drawing on real option theory and location and agglomeration theory. We test our
hypotheses on a comprehensive sample of 1078 Asian manufacturing affiliates of Japanesemultinational firms in the electronics industry during the turbulent years preceding and into the
Asian financial crisis (1995-1998). We find evidence that multinational firms both maintainflexibility options by maintaining a network of platform affiliates in multiple Asian countries,and exercise these flexibility options through divestments of affiliates that do not add flexibility
value. Affiliates of which the location decision at entry was dominated by the local presence ofJapanese investor agglomeration or buyer-supplier agglomeration within vertical businessgroups have higher divestment rates, suggesting that agglomeration leads to ‘adverse selection’of affiliates with weaker competitiveness.
Keywords: Divestment, agglomeration, multinational firms, affiliate networks, business groups*

Katholieke Universiteit Leuven, Faculty of Economics and Applied Economics, Department of Managerial

Economics and Strategy, Naamsestraat 69, B-3000 Leuven Belgium.
Phone: + 32 16 326912, Fax :+ 32 16 326732E-mail: Rene.belderbos@econ.kuleuven.be**

Katholieke Universiteit Leuven

Divestment of Foreign Manufacturing Affiliates:
Country Platforms, Multinational Plant Networks, andForeign Investor Agglomeration
René Belderbos
Katholieke Universiteit Leuven, Technische Universiteit Eindhoven, and Keio
University
Jianglei Zou
Katholieke Universiteit Leuven

ABSTRACTWe develop hypotheses concerning the impact of multinational firms’ international plant
networks and host country foreign investor agglomeration on the divestment of manufacturing
affiliates, drawing on real option theory and location and agglomeration theory. We test our
hypotheses on a comprehensive sample of 1078 Asian manufacturing affiliates of Japanesemultinational firms in the electronics industry during the turbulent years preceding and into the
Asian financial crisis (1995-1998). We find evidence that multinational firms both maintainflexibility options by maintaining a network of platform affiliates in multiple Asian countries,and exercise these flexibility options through divestments of affiliates that do not add flexibility
value. Affiliates of which the location decision at entry was dominated by the local presence ofJapanese investor agglomeration or buyer-supplier agglomeration within vertical business groups
have higher divestment rates, suggesting that agglomeration leads to ‘adverse selection’ ofaffiliates with weaker competitiveness.
Keywords: Divestment, agglomeration, multinational firms, affiliate networks, business groups
Correspondence to:René Belderbos
Katholieke Universiteit Leuven
Faculty of Economics and Applied Economics
Department of Managerial Economics and Strategy
Naamsestraat 69
B-3000 Leuven
Belgium
Phone + 32 16 326912; Fax + 32 16 326732
Email: Rene.belderbos@econ.kuleuven.be1Divestment of Foreign Manufacturing Affiliates:
Country Platforms, Multinational Networks, andAgglomeration
INTRODUCTION

The expanding literature on multinational firms has devoted substantial attention to strategic
issues related to their foreign expansion, such as the firm-level determinants of international expansion(Belderbos and Sleuwaegen, 1996; Kogut and Chang, 1991; 1996), the choice of entry mode abroad (e.g.
Delios and Beamish, 1999b; Hennart, 1991; Barkema and Vermeulen, 1999), the choice of location of
new affiliates (Head et al., 1995; Shaver and Flyer, 2000), and the impact of multinational expansion andgeographic scope on overall firm performance (Delios and Beamish, 1999a; Hitt et al, 1997; Tallman andLi, 1996). These empirical studies have been based on an abundance of, mostly complementary, theories
of multinational enterprise and foreign investment drawing on transaction costs theory (e.g. Caves, 1998,
Dunning, 1993; Hennart, 1988), the theory of oligopolistic interaction (Knickerbocker, 1973), location andagglomeration theory (Chung and Kalnins, 2001, Krugman, 1991, Chung and Alcacer, 2002), theresourced based theory of the firm (e.g. Chang, 1995), process and organizational learning theory(Johansson and Vahlne 1977; Kogut and Zander, 1995), and the theory of real options (Kogut andKulatilaka, 1994a, 1994b). 1
Comparatively little attention has been paid to multinational firms’ decisions to withdraw fromforeign operations, i.e. foreign divestment. Previous studies have examined the implications of several
streams of foreign investment theory for divestments and uncovered a number of factors systematicallyaffecting the survival of foreign affiliates, such as the mode of entry (Li, 1995; McCloughan and Stone,
1998; Shaver, 1998), size and experience of the affiliate (Benito, 1997; Shaver et al, 1997; Zaheer and1

See also Belderbos and Sleuwaegen (2005) for an overview.

2

Mosakowski, 1997), the market focus of the affiliate (Chen and Wu, 1996; Pan and Chi, 1999), the extent
of diversification of entry (Li, 1995), parent experience gained through previous international expansion(Li, 1995; Shaver et al, 1997; Delios and Beamish, 2001), human capital and technology advantages (Mataand Portugal, 2000; Delios and Beamish, 2001; Belderbos, 2003) and affiliate capabilities related to local
embeddedness (Song, 2002). A limitation of most of these studies is that they examined the determinantsof survival and divestment of foreign affiliates in a single country setting, e.g. in the US (Li, 1995; Shaver,1998; Shaver et al, 1997), Portugal (Mata and Portugal, 2000; 2002), Taiwan (Chen and Wu, 1996),
Ireland (McCloughan and Stone, 1998), Belgium (Pennings and Sleuwaegen, 2000), Japan (Yamawaki,1999) and China (Pan and Chin, 1999). Partly as a result, previous studies have largely ignored thepotential impact of the role of the affiliate in the larger international plant network of the multinationalfirm. 2 Real option theory conceptualizes how operating a network of manufacturing plants in different
countries can create value for the multinational firm by providing options of manufacturing location
flexibility under uncertainty. Affiliates could play the vital role of a country platform investment (Kogut
and Kulatilaka, 1994b) providing future expansion options, but at the same time affiliates may face greater
odds of divestment in case of international relocation of manufacturing operations to other affiliates in the
network. Real option theory has been applied to explain sequential investments by parent firms (Kogut
and Chang, 1996), the formation of multinational networks as a competitive advantage (Kogut andKulatilaka, 1994a; Tang and Tikoo, 1999), and entry mode decisions (Kouvelis, et al., 2001; Kogut, 1991)
but the implications for divestment decisions have not been examined. 3
A second relative discrepancy between foreign investment theories and divestment studies
concerns the role of foreign investor agglomeration. Foreign investor agglomeration may benefit affiliates
in a country due to potential knowledge spillovers, externalities in the provision of specialized businessservices and intermediate inputs, or positive demand effects (e.g. Chung and Kalnins, 2001; Wheeler and2

Studies that did examine divestments in multiple countries, e.g. Benito (1997) for Norwegian firms, Belderbos(2003) for Japanese firms in Europe, Park and Park (2000) for Korean firms, and Song (2002) for Japanese firms in
Asia (1988-1994) did not examine the impact of multinational operations from a real options perspective.
3
An exception is Pennings and Sleuwaegen (2000), analysing plant closures and plant relocations by domestic andforeign owned firms in Belgium.

3Mody, 1992). Empirical studies of location decisions by multinational firms have provided strong
confirmation of the positive impact of agglomeration on location choice (e.g. Chang and Park, 2005;
Smith and Florida, 1994; Head and Ries, 1996; Head et al., 1995). Empirical studies of the effects ofagglomeration on firm performance have however generally not been able to confirm an expected positive
impact (e.g. Appold, 1995; Baum and Mezias, 1992; Chung, 2001). This has been attributed to the greater
competition between firms in agglomerated areas to attract customers or to secure quality inputs (e.g.
skilled labor) which may lead to increased price competition and higher input costs. An alternative
explanation for a negative correlation between agglomeration and firm performance is that agglomerations
are more attractive to firms with lower long-term survival chances, in a process termed ‘adverse selection’(Shaver and Flyer, 2000). This notion has received indirect support in empirical studies of location choicethat found important heterogeneities in firms’ responses to agglomeration depending on investing firms’
characteristics (Belderbos and Carree, 2002; Delios and Henisz, 2000; Chung and Song, 2004; Nachum
and Wymbs, 2005), with smaller, less experienced, or less resource rich firms more attracted toagglomerated areas. The implications of these complex impacts of agglomeration for firm survival havenot been investigated in detail.
In this paper we develop hypotheses concerning the impact of multinational firms’ international
plant networks and host countries’ foreign investor agglomeration on the probability of divestment of
manufacturing affiliates, drawing on real option theory and the theory of agglomeration and location
choice. The importance of these theoretical insights has been explored in the context of international
expansion by multinational firms, but is yet to be examined adequately in the context of foreigndivestments. 4 We explicitly take into account that foreign affiliates are often part of an intra-firm
multinational network of affiliates, and that they can have inter-firm ties with other local affiliates
belonging to the same vertical business group. We examine the complex role of agglomeration andspecifically address the impact of adverse selection in a two-step methodology, calculating a measure of

4

In this, we follow the suggestion of Boddewyn (1983) that any theory of divestment should consider the conceived
determinants of foreign investments.

4

adverse selection from the estimated responsiveness of affiliates to agglomeration as obtained from a firststep location decision model. We test our hypotheses on a large sample of 1078 manufacturing affiliates
operated in nine Asian countries by Japanese electronics multinationals during the years preceding andinto the Asian financial crisis (1995-1998). This is an interesting setting for our analysis from several
perspectives. Multinational firms operating in Asia in these years faced great uncertainty concerning
exchange rates, inflation, and economic recovery and demand in different Asian countries. This increased
the option value of operating a network in various countries, while at the same time divergence in laborcosts developments pushed firms to use their networks for international relocation. The plant location
choices of Japanese firms have furthermore been found to be particularly responsive to agglomerations ofother Japanese-owned plants abroad, in particular if the investing firms are suppliers within verticalbusiness groups that follow the leading assembler abroad (e.g. Belderbos and Sleuwaegen, 1996; Head etal. 1995; Martin et al. 1995;1998; Delios and Henisz, 2003; Chung and Song, 2004).

LITERATURE AND HYPOTHESES

Literature Review
Studies on survival of foreign affiliates drew their early inspiration from industrial organization
theory on industry and firm dynamics, dealing with firm entry, exit, and post-entry performance.
Theoretically, Jovanovic (1982) modeled the expansion of firm as an adaptive learning process. He argued
that firms learn about their efficiency only gradually and, under uncertainty, tend to enter with a relativesmall size. Successful firms subsequently increase their size incrementally as their efficiency reveals itself,
and unsuccessful firms exit at an early age when they are still small. His model predicts that, at a given
point in time, larger firms and older firms are more likely to have been growing successfully in the pastand hence have a higher probability of survival, compared with their smaller and younger counterparts.
Evidence in support of this prediction has been found in several empirical studies: e.g. Evans (1987) found5

that the probability of firm survival increases with firm size and firm age, and Dunne et al (1988) foundthat small and younger firms have the highest rate of failure. 5 The relationships between establishment
size, age and the probability of survival have also been tested in the context of foreign owned affiliates. Li(1995) found a positive relationship between affiliates’ size and survival rate for foreign owned affiliates
in the US, Yamawaki (1999) for foreign owned affiliates in Japan, Chen and Wu (1996) for foreignsubsidiaries in Taiwan, and Belderbos (2003) for Japanese affiliates in Europe. The relationship between
foreign affiliate age and survival, however, appears substantially more complex. On the one hand, earlier
evidence supports a positive relationship between firm age and firm or affiliate survival (e.g. Mitchell,
1994; Mata and Portugal, 1994; Yamawaki, 1999; Benito, 1997; Shaver et al, 1997). On the other hand, Li(1995) and Hennart et al (1998) found the exit rate to be particularly low in the first years after
establishment. This suggests the presence of a “honeymoon” effect: firms give affiliates, even if they are
not performing well, a number of years to prove their success. Mata and Portugal (2002), analyzing
foreign owned firms in Portugal, found evidence of a “liability of adolescence”: exit rates increased forolder affiliates, suggesting that there is increasing organizational rigidity or obsolescence of organizational
resources as new establishments age (cf. Hannan, 1998).
The international business literature has further focused on the determinants of survival of foreign
affiliates specifically, drawing on a number of theories. Theories of foreign direct investment (e.g. Caves,
1996; Dunning, 1993) posit that firms entering foreign markets face much higher information andadaptation costs and are put in an inferior position through their “liability of foreigness” vis-à-vis local
firms. Hence, foreign entrants require a compensating competitive advantage, often based on thepossession of intangible assets that can be transferred and exploited abroad, in order to survive (e.g.
Buckley and Casson, 1976). A number of empirical studies have confirmed a positive impact oftechnology, advertising, or human capital intensity on foreign affiliate survival (e.g. Delios and Beamish,2001; Mata and Portugal, 2000; Belderbos, 2003).

5

See also Caves (1998) for an overview of this literature.

6

A complementary view on foreign direct investment, the process or “stage” theory ofinternationalization, suggests that firms tend to circumvent the “liability of foreigness” problem byfollowing an incremental pattern of foreign market involvement (Johanson and Valhne, 1977). Firms build
up internationalization experience through acquiring foreign market knowledge from previous
involvement, enhancing the capability to efficiently exploit their intangible assets on (more distant)foreign markets (Kogut and Zander, 1995), and reducing the probability of foreign affiliate failure. Chang(1995) found evidence that Japanese firms follow a sequential pattern for their entries into U.S. markets,with first entries focusing on core, competitive, product lines and subsequent entries focusing on non-corebusiness. Li (1995) and Barkema et al. (1996) found that subsequent entries of multinational firms wereless likely to exit than first time entries. Delios and Beamish (2001) showed that host country experienceof the investing parent not only increases survival probability, but also enhances the profitability of theaffiliates by allowing a more efficient exploitation of intangible assets in the foreign market. Shaver et al.
(1997) extended the argument on experience effects by suggesting that firms can also learn from otherfirms’ host country experience, by examining what previous entry strategies have worked or failed. They
found a positive relationship between the survival of foreign affiliates and the experience of other foreign
affiliates in US industries. Kim and Delios (2003) highlighted a duality of host country experience forinvesting firms: experience allows for learning and positively impacts survival of subsequent entries, but
can also lead to organizational inertia if previous experience is largely irrelevant to the subsequent entries.
An expanding literature in international business has examined the entry mode decisions forforeign operations and the impact of entry mode on affiliate survival, with a focus on the longevity andstability of international joint-ventures (Gomes-Casseres, 1987; Kogut, 1991). Most findings suggest that
foreign joint venture have a systematically higher probability of exit than wholly owned greenfield entries(e.g. Li, 1995; Yamawaki, 1997; Hennart et al, 1998; Kim and Delios, 2003). 6 This has been related to
failure to deal with management conflicts and cultural differences, but also to a learning perspective of

6

Although other studies (e.g. Benito, 1997; Pan and Chi, 1999) have not found a differential rate of survival between
the two types of foreign establishments.

7

joint ventures: foreign firms may withdraw from a joint venture and expand their wholly owned operationsin the country once they have gained sufficient experience through the joint venture (Kogut,1991; Yan andZeng, 1999; Inkpen and Beamish, 1997). Hennart et al. (1998) indeed suggest that the higher termination
rate of joint ventures is predominantly explained by a higher probability of selling the equity stake insteadof by a greater probability of liquidation. Dhanaraj and Beamish (2004) provide a more fine-graied
analysis of the role of equity ownership in the dissolution of foreign affiliates and found that minority
stakes are associated with divestment, but not majority stakes. Besides entry through joint ventures,acquired affiliates also appear to exhibit higher divestment probabilities, which has been attributed todifficulties related to post-acquisition integration (Li, 1995; Shaver et al, 1998; McCloughan and Stone,
1998; Mata and Portugal, 2000).
Other strategic variables that have been suggested to impact foreign affiliate survival are thedegree of diversification and the market orientation of the firm. Diversified affiliates are more likely to fail,mainly due to the fact that investing firms have to deal at the same time with unfamiliar markets andunfamiliar products (Benito, 1997; Li, 1995; Yamawaki, 1997). With regard to the market orientation of
the firm, it has been suggested that export oriented foreign affiliates are more footloose because they are
established by their parent firms to arbitrage the factor cost differentials across production locations. This
makes the affiliates more sensitive to changes in cost conditions (Caves, 1996), or less embedded in thelocal economy in terms of supplier and other linkages (Belderbos et al, 2001; Song, 2002). Chen and Wu(1996), in a study of foreign investment projects in Taiwan, related the proportion of affiliate sales
generated from export to the survival of the affiliate, and confirmed that affiliates with higher export
proportion are more likely to withdraw. Pan and Chi (1999), on the other hand, found no find evidence fora systematic impact of market focus of foreign affiliates’ survival and financial performance in a study offoreign-owned firms in China.

8

HYPOTHESES

Two issues that have not received due attention in the divestment literature but have been found
relevant for FDI decisions are the real options perspective on FDI and manufacturing networks, and therole of agglomeration in location decisions by multinational firms.
Most of the literature on foreign affiliate survival implicitly associates exit with the failure of theforeign affiliate. However, exit may be due to reasons other than affiliate failure, and poor performance isonly one of the identified factors of foreign divestment (Boddewyn, 1979). The literature on
multinationality and firm performance emphasizes that multinational firms can achieve lower operationalcosts by adapting manufacturing plant networks to changing cost and demand conditions in multiple
countries (Grant, 1987; Gomes and Ramaswamy, 1999; Tang and Tikoo, 1999). Firms will locate andrelocate manufacturing plants in response to relative cost and demand conditions, comparing alternative
manufacturing locations. Hence, it is relative profitability and efficiency rather than affiliate performance
per se that may cause the relocation of manufacturing and ultimately a divestment decision.
In this context, real option theory offers a way to conceptualize how dispersed manufacturing
plants add value to the firm. Under the condition of uncertainty concerning future relative cost and market
conditions in host countries, the ability to shift manufacturing operations quickly between locations in
response to changing cost differentials can provide an important competitive advantage. Kogut andKulatilaka (1994a) theoretically showed that the option value of this flexibility could be substantial when
there is high uncertainty concerning demand or manufacturing cost differentials. Multinational firms
therefore can benefit from keeping options of future manufacturing expansion open in various countries
with potentially divergent macroeconomic developments. They create these options by operating local
manufacturing affiliates, which serve as potential platforms for future expansion (Kogut and Chang, 1996).
Kogut and Kulatilaka (1994b) coin these manufacturing affiliates ‘country platforms’. Operating theseplatforms allows firms to capitalize on country-specific investments they made in developing local

9operational know-how and relationships with local suppliers and customers, and government institutions(Song, 2002; Belderbos et al, 2001) to facilitate swift and effective expansion.
As a corollary, under uncertainty concerning future economic circumstances, the option value ofthe platform also creates investment ‘hysteresis’: firms are reluctant to divest the platform even underadverse circumstances, as divestments eliminate the option of effective future expansion. This reduction in
option value in case of divestment occurs if the manufacturing affiliate effectively serves as a country
platform: i.e. it is the only manufacturing affiliate in the country operated by the firm. In contrast, if anaffiliate is one among multiple manufacturing affiliates in a country, divestment of an individual affiliate
does not affect future expansion and network flexibility options. Hence, the following hypothesis follows
under conditions of uncertainty:

Hypothesis 1: a foreign manufacturing affiliate that is the only affiliate of the parent firm in a country (anaffiliate serving as ‘country platform’) has a lower probability of divestment.

The previous arguments suggested that multinational firms derive value from creating network
flexibility options by maintaining a network of country platforms. At the same time, firms will only derivevalue from network flexibility if they indeed can exercise flexibility options in response to temporaryshocks in local environments. If not, there would be no benefit in operating a network from a flexibility
perspective under longer term uncertainty. Kogut and Kulatilaka (1994a) show how firms can exercise
flexibility options by changing capacity loadings of affiliates in different countries rapidly in response tocost and demand changes. In order to preserve the flexibility value of the network, firms will not divest
manufacturing operations in a country as long as uncertainty remains concerning future cost and demandconditions.
In the stylized representation of Kogut and Kulatilaka (1994a), the multinational firm operates one
single plant in each country. In practice however, multinational firms can and do operate multiple
manufacturing affiliates in the various countries in which they are active. In the context of multiple plants

10operated by multinational firms in the same country, the exercise of flexibility options is not necessarily
limited to changes in capacity loadings, but can also involve closure and relocation of entire productionlines and manufacturing affiliates. Although firms will wish to preserve flexibility options by refraining
from divesting manufacturing affiliates that serve as country platforms, firms can implement adjustmentsin their international manufacturing configuration without affecting flexibility value by closing
manufacturing affiliates that do not serve as country platforms. Closure of one of multiple manufacturing
affiliates in a country will not substantially reduce the firm’s ability to shift back production quickly to thecountry if investment conditions improve again, as the firm maintains one or more manufacturing bases in
the country. This implies that the exercise of network flexibility options can involve divestment of
manufacturing affiliates, but only if these affiliates do not serve as country platforms.
The exercise of plant network flexibility options involving affiliate divestments is more likely tooccur, the greater the number of country platforms the multinational firm operates and hence the larger the
potential number of relocation options that can become opportune due to a possible divergence in cost anddemand conditions between countries. In contrast, multinational firms that only operate affiliates in one ora limited number of countries have fewer effective relocation opportunities and their affiliates are lesslikely to be divested due to the exercise of network flexibility options. Hence, the larger the network ofcountry platforms operated by the firm, the greater the likelihood that a non-platform affiliate is divested,
but this pattern is not predicted for affiliates that serve as country platforms themselves. This leads to thefollowing hypothesis:

Hypothesis 2: The probability of divestment of a foreign manufacturing affiliate that is not the only
manufacturing affiliate operated by the parent in a country (an affiliate that does not serve as ‘country
platform’) is higher the larger the network of country platforms operated by the parent firm.

It has long been suggested (Marshall, 1922) that firms can enjoy positive externalities stemmingfrom geographic industry clustering. These can occur on the input side, as increased demand for inputs

11stimulates the provision of specialized (labor) inputs and specialized business services. Externalities may
also occur on the demand side, as co-location of firms lowers search costs for customers and so heightens
local industry demand, or through locally bounded spillovers of technological and organizational
knowledge. These possible externalities motivate firms to choose locations where similar establishments
are clustered, an intuition which has been supported by formal economic models (Krugman, 1991; Davidand Rosenbloom, 1990). A substantial collection of empirical studies of plant location decisions haveconfirmed that industry clusters in countries or regions attract plant establishments by both domestic firms
and foreign investors. 7
Agglomeration effects have been found to be particularly strong in the case of Japanesemultinational firms' foreign investment decisions (e.g. Head et al., 1995; Mayer and Muchielli, 1998).
Japanese firms are much more likely to choose those foreign locations for their manufacturing activities
where other Japanese investors have established affiliates before, even after controlling for generalindustry clustering effects (e.g. Belderbos and Carree, 2002; Head et al., 1995; Chung and Song, 2004).
This particular responsiveness of Japanese firms to agglomerations of establishments of other Japanesefirms has been attributed to the presence of greater externalities associated with co-location. These are dueto the ease of communication and information exchange between Japanese companies and to the use ofsimilar inputs such as the shared use of ‘national’ amenities (e.g. Japanese schools), the use of similarlabor training systems and labor pools, common reliance on just-in-time (JIT) delivery systems that
require close spatial concentration of manufacturing plants and strict production flow control by suppliers,and quality control requirements that can be satisfied more easily by Japanese firms with experience intotal quality management (e.g. Smith and Florida, 1994; Belderbos and Carree, 2002; Head et al., 1995).
The presence of externalities related to industry clustering is consistent with the notion thatindustry clusters enhance the overall competitiveness of the location as well as the competitiveness of the
population of firms (Porter, 1990). However, empirical findings on the impact of industry or foreign

7

E.g. Carlton (1983), Bartik (1985), Wheeler and Mody (1992), Head et al, (1995), Head and Ries (1996), Belderbos
and Carree (2002), Shaver and Flyer (2000), Delios and Henisz (2000).

12

investor agglomeration on the performance of individual firms have not generally provided evidence of apositive relationship. In a study of the US metal working sector, Appold (1995) found a negative
correlation between industry clustering and firm performance. Baum and Mezias (1992), analyzing the
Manhattan hotel industry, found that geographically localized competition increased failure rates. Zaheer
and Mosakowski (1997) found an inverted-U shape relationship between survival and the number ofcompetitors in host countries’ financial service industries. Kim and Delios (2003) found that geographic
proximity to other Japanese affiliates in the same industry negatively impacted Japanese affiliate survival
in China. Shaver and Flyer (2000) found that industry agglomeration in US states was associated with agreater probability of exit of foreign affiliates. Chung (2001), in a longitudinal analysis of foreign affiliate
performance, found that foreign establishments that located more remote from existing industry clusters
performed better in terms of price cost margins than firms locating within local clusters. Chung and
Kalnins (2001) found a positive demand enhancing effects of clusters of large hotels on other hotels’
performance in the Texas hotel industry, but at the same time a negative impact of the presence of hotels
operating in a similar market segments. A common explanation for these findings is that geographic
proximity has a detrimental effect that may outweigh agglomeration benefits: proximity increases theintensity of competition on output markets, reducing output prices, and may also increase competition on
factor markets, driving up factor prices (e.g. Chung and Kalnins, 2001; Kim and Delios, 2003). 8
An alternative explanation for a negative correlation between agglomeration and individual firm
performance is suggested by a number of recent studies that emphasize that the attractiveness and impact
of industry agglomeration differs depending on the characteristics of the investing firm. In other words,
firms are heterogeneous in their response to agglomeration and the potential advantages or disadvantages
associated with it. Chung and Alcacer (2002) examined the moderating impact of differences in R&D
intensity between home and host countries on the tendency of foreign investors to locate in US states.
They found that firms coming from countries with relatively low R&D intensities choose US states with

8

Sorenson and Audio (2000) found that geographic clustering in the shoe industry increased failure rates, andattribute this to increased competition to attract labor.

13

high R&D intensities, suggesting that areas with a greater concentration of R&D intensive firms attract
predominantly knowledge seeking investments by technology laggards. Nachum and Wymbs (2005)
found evidence of heterogeneity in the choice of the location of acquisition targets by professional service
firms in London and New York. Firms with higher levels of product differentiation chose locations
significantly further away from other firms in the same service industry than firms with a lessdifferentiated service portfolio. Delios and Henisz (2000) found that Japanese firms without muchinternational experience were more likely to invest in countries in which other Japanese firms had
previously invested. Chung and Song (2004) obtained similar results in an analysis of Japanese electronics
firms’ location decisions in the US. Belderbos and Carree (2002) found that smaller firms’ location choice
in China was significantly more responsive to Japanese investor agglomeration than the location choice bylarger firms.
Taken together, these studies provide evidence that agglomeration systematically attracts firmsthat may be competitively in a weaker position: smaller, less experienced, less technologically advanced
and less able to differentiate products. The explanation for this pattern is relatively straightforward: large
firms with the most innovative technologies, organizational and process skills, and the most differentiatedproducts contribute the most to agglomeration externalities, but benefit relatively less. These firms havemost to loose from knowledge spillovers within the industry cluster, skilled employee mobility,
mimicking by local competitors of product designs and organizational approaches, all of which strengthen
weaker local competitors. Smaller and less resource rich firms on the other hand, do not add much to theexternalities in local clusters, but see important benefits from such externalities. Hence, agglomeration
leads to ‘adverse selection’: a selection process through which the firms with relatively weakercompetitiveness are more likely to opt to locate within the cluster and the most competitive firms more
likely to locate outside the cluster.
The relatively greater presence of firms with weaker competitiveness in industry agglomerations
allows for a reconciliation of the presence of agglomeration externalities with the empirically observed
greater incidence of firm exit within industry agglomerations, but the explanatory power of this adverse

14

selection argument has not yet been investigated. 9 Adverse selection suggests that those firms for which
the agglomeration factor was dominant in the location choice decision at the time of entry because they
expected important net benefits from agglomeration, are less likely to possess substantial competitive
resources of their own. Among those firms, a relatively large proportion may be less likely to sustain asufficient level of competitiveness in the years subsequent to entry, as firms lack the capabilities to adapt
to possible changes in the environment such as increased competition or cost increases. This implies thatthose firms that are most responsive to agglomeration in their location decisions are less likely to survive
in the longer term. In the context of foreign investments by Japanese firms, the observed importance ofprevious Japanese investments for location choices suggests that adverse selection arises through Japanese
investor agglomeration. This leads to the following hypothesis:

Hypothesis 3: Japanese manufacturing affiliates of which the location choice at entry was more
responsive to Japanese investor agglomeration have a higher probability of divestment.

The attraction of foreign investor agglomeration has been found to be particularly pronounced forJapanese firms belonging to vertical business groups (vertical keiretsu), centered around large ’core’ firms
in the automobile and electronics industry such as Toyota or Toshiba. Several empirical studies haveconfirmed that the presence of group affiliates in a location has a substantial and significant positive effecton location choice probabilities for group firms, on top of the impact of general Japanese affiliate
agglomeration (Head et al., 1995; Smith and Florida, 1994; Dyer, 1996; Belderbos and Carree, 2002).
Vertical keiretsu are characterized by intensive supplier-buyer linkages and intra-group trade where thesuppliers are to a large extent dependent on trade with the core firm or other firms within the group. These
supplier buyer relationships are often accompanied by intensive inter-firm flows of information anddedicated investments in design and production equipment by suppliers to serve the core firm. Vertical
9

Shaver and Flyer (2000) suggested, but did not explore, that a negative impact of agglomeration could be due toeither more intense competition, or the greater attraction of agglomerated areas to firms with fewer managerial andtechnological resources.

15business groups have often replicated these supplier relationships abroad, with ‘core’ firm investments in alocation followed by first and second tier supplier establishments (Martin et al. 1998; Martin et al. 1995;
Head et al. 1995). The core firm may even provide initial assistance to member firms in the process ofoverseas expansion and provides assured market potential for locally manufactured output of the suppliers.
Also, subcontractors that are for a large part of their sales dependent on core firm demand, often have noother option but to invest abroad in response to the international relocation of core firm plants.
Under the above conditions, foreign investment decisions by member firms are not governed byfirm-specific competitive advantages as theories of foreign direct investment suggest, but by the presenceof intra-group trade linkages. Previous studies have provided evidence that member firms indeed invested
abroad in the absence of competitive advantages based on R&D, human capital, and marketing skills, butinstead responded to plant networks of the vertical group, while independent firms did base foreign
expansion strategies on firm-specific advantages (Belderbos and Sleuwaegen, 1996). This suggests that
another form of adverse selection arises if the presence of strong intra-group trade linkages related to local
agglomerations of group affiliates leads member firms with weakly developed competitive resources toco-locate manufacturing affiliates. The future of these affiliates hinges primarily on the continuation of
intra-group trade relationships, as these firms’ capabilities to develop and manufacture products costcompetitively for non-keiretsu clients are more limited. Yet these linkages are not guaranteed. If
technological developments and increased price competition lead core firms to substitute procurement ofmass produced standard components for design-specific components produced intra-group, the survival
chances of member firm manufacturing affiliates are greatly reduced. Recent evidence suggests thatJapanese firms abroad have indeed gradually sourced more components from independent local firms that
improved quality and to rely more on standard parts procurement, partly as a response to increasing pricecompetition from Asian firms. 10

10This pattern is particularly visible in the electronics sector (Paprzycki, 2005; Belderbos et al., 2001; Baba andHatashima, 1995).

16

Summarizing, firms in vertical business groups can overcome barriers to foreign expansion
through the replication of supplier-buyer linkages within a local network of group manufacturing plants,
and are therefore more likely to invest in the absence of competitive advantages on third markets. Hence,vertical business group agglomeration induces ‘adverse selection’ and this is most pronounced for firmsthat base their investment decision primarily on business group agglomeration. Affiliates that are mostdependent on group agglomeration are likely to have lower long term survival chances. This leads to thefollowing hypothesis: 11

Hypothesis 4: Japanese manufacturing affiliates of which the location choice at entry was more
responsive to vertical business group investor agglomeration have a higher probability of divestment.

DATA AND EMPIRICAL METHODS

Data
Our dataset consists of 1095 manufacturing affiliates operational in early 1995 that were whollyor partially controlled by 412 Japanese firms in the broadly defined electronics industry in 9 Asian
countries or regions, i.e. South Korea, Taiwan, China, Hong Kong, Singapore, Indonesia, Philippines,
Malaysia, and Thailand. The data are compiled by the Research Institute of Electronic Industry as “Asia
Shinshutsu Denshi Meika” (Survey of Japanese electronic firms in Asia) in Tokyo in 1995 and early 1999.
It is an authoritative source on Japanese foreign investments in Asia in the electronics industry withcomplete coverage of investments by both large firms, small and medium sized firms, and specialized11

We note that such agglomeration effects are much less a feature of horizontal keiretsu members’ investments
abroad. Henisz and Delios (2001) find only weak influences of horizontal keiretsu membership on investment
decisions and argue that potential impacts are due to imitative behaviour under uncertainty rather than agglomeration
economies. In the industry setting of the current paper, the effect of horizontal groups spanning a wide array of
industries is furthermore difficult to examine.

17

suppliers to the electronics industry (glass, plastic, metals, chemical materials). 12 The data give a reliable
picture of investments by both leading electronics firms and smaller vertical business group-related or
unrelated suppliers along the value chain of the electronics industry. The database contains information on
the affiliates’ paid-in capital, number of employees, equity stake held by Japanese investors, direction ofsales, and products manufactured, and it also contains parent firm information on sales, number of
employees, paid-in capital, and recent developments in the firms’ overseas operations. We included in our
analysis those manufacturing affiliates in which (Japanese) parent firms have an equity stake of at least 10
percent. A divestment case was identified if we could confirm with certainty that a 1995 affiliate waseither closed or its stake sold to a local or foreign firm by its parent within the 1995-1998 period. 13 The
confirmation was given by the parent information provided for each Japanese firm on such decisions in
the 1999 edition of the survey, combined with information from other publications by the ResearchInstitute on Electronics Industry on developments in Japanese electronics firms (such as quarterlycompilations of press releases), other sources on Japanese affiliates abroad (Toyo Keizai, 1999), andcoverage in Japanese newspapers drawn from the Nikkei web news service. As a result, 99 out of 1095
overseas manufacturing affiliates in operation in early 1995 were identified as having been divested byearly 1999. Since for 17 affiliates a number of explanatory variables (primarily parent sales and affiliate
employment) had missing values, our empirical analysis is performed on 1078 observations, out of which
97 are divestment cases.
The country distribution of the affiliates included in our analysis and the country distribution ofdivestments are presented in Table 1. China had the largest share of affiliates in our sample (22 percent),
followed by Malaysia (21) and Taiwan (13). The distribution of divestments is rather different, withdivestments mostly occurring (in terms of the share of divested affiliates) in the NIEs: Singapore (19percent), Hong Kong (16), and South Korea (14).

12The coverage is much broader, in particular for smaller and privately held firms, than the coverage of the oftenused directory compiled by Toyo Keizai Inc. (e.g. Delios and Beamish, 2001).
13
In line with previous work, we examine all divestments.

18

Insert Table 1

Model specification
Our dependent variable is binary, taking the value 1 if a 1995 affiliate is divested prior to early
1999 and 0 if it survived as a parent affiliate in the 1995-1998 period. We use a Probit model to relate theprobability of divestment to the explanatory variables. In the Probit model there is a latent variablemeasuring the likelihood of divestment of each affiliate ( y i* ), which can be related to a set covariates. We
observe divestment if this latent variable exceeds a certain threshold value (e.g. Greene, 1997).

yi* = β 0 + β1 xi + ε i(1)

Yi = 1

if yi* > 0

Yi = 0if yi* < 0We use a discrete choice model rather than a duration model. The main reason is that the exact
year of the divestments could not be determined in all cases. While differentiating between the year ofdivestment would provide more variation in the dependent variable by specifying spells, given the four
year time frame this advantage would be rather limited and the results would not be very different. 14 A
potential problem with analysing divestment decisions in a fixed time frame is left censoring. We only
observe affiliates that have survived until 1995 and not those that were divested sometime between
establishment and the year 1995. We believe that this censoring problem is not likely to lead toappreciable biases in our empirical results for two reasons. First, the evidence suggests that divestments
were rather rare before 1995. The press release and newspaper screening on investments and divestments
in Asia as well as earlier reports on foreign affiliates by the Research Institute for Electronics Industry did
not result in more than a handful of divestments. Song (2002) also reports only few cases of divestments

14

Shaver and Flyer (2000) also report similar results of duration and probit models in their analysis of divestments
by foreign affiliates in the US.

19

in his sample of Asian affiliates of Japanese electronics firms in 1988-1994. Second, in order to control fora possible bias due to left censoring, the model includes a flexible quadratic specification for affiliate age
as a control variable. If censoring (early divestments before we are observing these) is occurring, it is most
likely to occur for older affiliates rather than more recently established affiliates, since the performance ofolder affiliates has been evaluated more frequently and over a longer period. The older affiliates thatsurvived until 1995 are therefore more likely to have performed relatively well. This implies that age may
pick up an unobserved type of competitiveness, which should imply a negative correlation withdivestment. However, the empirical results described below show the opposite effect (divestment
probabilities increase with affiliate age) which indicates that left censoring bias is not likely to feature in
our analysis. 15

Operational measures
To test Hypothesis 1, we include a dummy variable (country platform affiliate), which takes thevalue 1 if the affiliate is the only manufacturing affiliate of its parent in the country in 1995, and 0
otherwise. Hypothesis 1 predicts a negative impact on the probability of divestment, under the assumptionof uncertainty concerning future investment conditions. In the empirical setting of our research, the latterassumption clearly holds. Multinational firms faced considerable uncertainty concerning economic
conditions in the region, in particular after the outbreak of the Asian financial crisis in the middle of 1997.
In the most affected countries such as Thailand, Korea, and Indonesia, a collapse of the exchange rate wasfollowed by a sharp rise in inflation rates and economic contraction. Neighboring economies, such as
Malaysia, the Philippines, and Hong Kong were also affected, and it was uncertain to what extent these
Asian countries would be able to regain macroeconomic and exchange rate stability accompanied byeconomic growth. Similarly, there was concern that China and Taiwan would not be able to neutralize theimpact of the crisis on their economies. Table 2 illustrates these developments by providing a number of
key indicators on economic developments in the nine Asian countries during 1995-1998. While real GDP
15

Right censoring is not an issue with discrete choice models such as the probit model.

20

growth was still positive over the period (with the exception of Thailand) partly due to rapid growthduring 1995-1996, several countries experienced a large fall in the value of their currencies accompanied
by a rapid rise in inflation. At the same time, the dollar value of local wages declined substantially in themost affected countries, increasing the cost competitiveness of these countries for manufacturing activities.
Table 2 also shows an indicator of macroeconomic uncertainty relevant for foreign investmentthat has been used in the literature: the variance in the monthly real exchange rate of local currency(expressed in Yen terms for the purpose of our analysis). This measure shows a high volatility for the fourmost heavily crisis-affected countries on the one hand (Thailand, Korea, Indonesia and Malaysia), andlower levels of volatility for the other five countries (Hong Kong, China, Singapore, Philippines andTaiwan). In an extension of the empirical analysis, we will examine if higher levels of volatility increase
the impact of platform investment status, consistent with the greater real option value of platform
investments under higher levels of uncertainty.

Insert Table 2

To test Hypothesis 2, we include the variable size of country platform network, the number ofcountries (other than the country of the focal affiliate) in the Asian region in which the parent firm had
manufacturing operation in 1995. Hypothesis 2 predicts a positive impact of size of country platform
network, but only for focal affiliates that do not themselves serve as country platforms. We include thevariable size of country platform network separately for platform and non-platform affiliates and expect aninsignificant impact of the former and a positive impact for the latter. 16 We note that Table 2 also shows
an important heterogeneity in the responses of Asian economies to the Asian financial crisis. Given theuncertainty concerning future developments and the likelihood of further divergence between countries,

16

We consider manufacturing platforms in other Asian countries as the most relevant for possible manufacturing
relocation. In the information on divestments and relocations we could assess, not one case was discovered of
relocation outside of Asia.

21

this suggests that the flexibility value of operating a network of country platforms in Asia has been
substantial.
In order to test Hypotheses 3 and 4 concerning the responsiveness to agglomeration, we adopt a
two-step methodology. We estimate a location decision model for all affiliates in our sample: for eachaffiliate at its specific year of entry. In this first-step location choice model, we include the relevant
agglomeration variables in addition to country controls. From this model we derive for each affiliate theelasticity of the location choice probability with respect to the agglomeration factors as a direct measure of
responsiveness to agglomeration. Hence, the methodology is to examine the selection impact ofagglomeration appropriately at the time of entry, while controlling for other factors affecting location
choice.
To examine the location choices, we use the widely used conditional logit model (e.g. Head et al,
1995; Chang and Park, 2005), modeling the probability that a country is chosen from a set of countries asa function of relative attractiveness of the country. The probability that firm i chooses country s at time t is
specified as:(2)

Pi ,s ,t =exp(θ s + βX s ,t + γX s ,t X i ,t )∑ exp(θ + βX
s

s

s ,t

+ γX s ,t X i ,t )Where X s ,t is a vector of location variables at entry time t with coefficients β , and θ s are location fixed
effects. X i ,t is a vector of investor characteristics that are interacted with location variables to examine
the role of investor heterogeneity, with coefficients γ . The location fixed effects control for all relatively
unchanging country characteristics, such as geographic location, cultural distance, and regulatory
institutions, that play a role in the general attractiveness of countries for Japanese manufacturing
investments. In order to control for time-variant location factors affecting country attractiveness, we

22

include in the model the value of foreign direct investment inflow to the country at the time of entry. 17 The
variables of interest in the location model are Japanese investor agglomeration at entry (the number ofJapanese electronics manufacturing establishments at the time of entry of the affiliate) and Keiretsu
investor agglomeration at entry (the number of electronics manufacturing establishments at the time ofentry established by firms within the same vertical keiretsu). If investor agglomeration benefits areimportant these two variables should have a positive impact on location choice. As discussed in theprevious section, the responses to Japanese investor and keiretsu investor agglomeration may differ
depending on investing firm characteristics. Earlier studies have found that smaller firms are much more
responsive to Japanese agglomeration than larger firms (Shaver and Flyer, 2000; Belderbos and Carree,2002). To allow for this effect we add the interactive term of Japanese investor agglomeration at entry
and parent firm size at entry (a variable of the form X i ,t ). 18 If larger firms are less attracted toagglomeration, the coefficients (of the form γ ) of the interactive term should be negative. In addition, weallow for heterogeneity in response to Keiretsu investor agglomeration. Here the existing empiricalevidence strongly suggest that member firms are responsive to agglomeration and follow foreign
investments by the core firm, while core firms appear more involved in pioneering new locations without
previous Keiretsu establishments (Belderbos and Carree, 2002; Pugel and Kimura, 1996; Smith andFlorida, 1994; Head et al., 1995). We therefore include Keiretsu investor agglomeration at entry
interacted separately with dummy variables for member firm and for core firm.
The results of conditional logit analysis, shown in Table 3, conform to our expectations and earlier
empirical results. Japanese investor agglomeration at entry is significantly positive while the interactive

17

FDI inflow data are drawn from balance of payments statistics published by the IMF. Given the large variation in
FDI values (ranging from zero to 37 billion dollars), we include the variable in logarithmic form after adding 1(million dollar) to each observation.
18
We used back copies of Toyo Keizai’s Directory of Foreign Affiliates and firm directories published by Nihon
Keizai Shimbun to establish previous entries by Japanese firms and historical parent employment data. Following
earlier work (Belderbos and Carree, 2002; Shaver et al, 2000), we use employment as the indicator of firm size;
historical employment data are also more readily available. We also tested for a possible interaction between hostcountry cumulative experience of the parent firm at entry and agglomeration as suggested by Delios and Henisz(2000) and Chung and Song (2004) but found this variable to be insignificant, partly due to multicollinearity with thesize interaction term.

23terms with parent size at entry is significantly negative, suggesting that agglomeration benefits are a more
important factor in location decisions for smaller firms. Similarly, Keiretsu investor agglomeration atentry has a positive and significant impact for member firms as expected, but it has an insignificant effectfor core firms. The foreign direct investment inflow variable is positive and highly significant, while thecountry fixed effects suggest that no country has been has been a significantly more attractive destination
for Japanese electronics investments than China (the reference country), while Hong Kong, Indonesia,
Philippines, Singapore and Thailand, have been significantly less attractive.

Insert Table 3

Hypotheses 3 and 4 imply that those affiliates, of which the location choice was particularly
responsive to Japanese investor and Keiretsu investor agglomeration, respectively, are more likely to be‘adversely selected’ and are less likely to survive. We can now operationalize these responsivenessmeasures directly by calculating an elasticity that measures the relative contribution of the agglomeration
factor in the investment location decisions. We calculate for each affiliate the proportional change in theprobability that the location was chosen with respect to a proportional change in agglomeration, taking
into account the estimated heterogeneity in firm responses. The elasticities for Japanese investor
agglomeration

at

entry

and

Keiretsu

investor

agglomeration

at

entry

are

calculatedas))
Ris = ( βX s ,t + γ X s ,t X i ,t )(1 − Pˆi ,s ,t ) where Ris indicates responsiveness to Keiretsu or Japanese
agglomeration, a hat (^) indicates estimated coefficients and X s ,t are the agglomeration variables. 19
Hypotheses 3 and 4 predict a positive impact on divestment. 20

19

E.g. See Greene (1997, p. 919); Head et al. (1995) and Chang and Park (2005) provide similar applications.
In the responsiveness to Keiretsu investor agglomeration measure we maintained the insignificant coefficient forcore firms. Setting the insignificant core firm coefficient to zero generates a stronger positive impact of
responsiveness in the divestment analysis. Similarly, if we calculate responsiveness to Keiretsu agglomeration
separately for core firms and for member firms, the former is not significant while the latter is significantly positivein the divestment analysis.
20

24Control variables

The model includes an extensive set of control variables representing factors at the parent, affiliate,and host country level suggested to have a potential impact on divestment in earlier studies.

Parent firm characteristics
We include three parent control variables. Parent firm patent intensity (the number of US patents
granted to the parent firm during 1993-1999 times 1000, divided by parent sales in 1995). Patent intensity
proxies for competitive advantages based on advanced technology that are likely to increase theprobability of affiliate survival. Furthermore, we include parent size, and parent prior country experience.
Parent size has been found to impact the probability of divestment positively (Li, 1995; Hennart et al.,
1998; Belderbos, 2003), but also negatively (Park and Park, 2000). On one hand, larger investing firms
may find it easier to reach a withdrawal decision and give less weight to the survival of individual
affiliates. However, a reverse argument also has appeal: larger firms have more financial or management
resources and can exercise more patience for poorly performing affiliates. Parent size is the logarithm ofparent firm sales in 1995. 21 Parent prior country experience (the number of affiliates established by theparent firm in the country prior to the establishment of the focal affiliate) captures that multinational firms
can reduce their “liability of foreigness” by learning from prior experience in the host country. Previous
studies have generally found a positive impact of host country experience on the probability of affiliate
survival (Hennart et al. 1998; Park and Park 2000; Shaver et al, 1997; Kim and Delios). 22

21

We took the logarithmic term to reduce the large variation in parent firm sales in the sample, ranging from 285
million Yen to more than 4000 billion Yen, and because we expect a declining marginal impact at the larger firm
sizes. A linear specification gives similar results though with a higher estimated standard error. The same approach
was taken with affiliate employment.
22
We also employed, as an alternative experience measure, the cumulative experience of the parent at the time ofentry of the focal affiliate (number of previously established affiliates multiplied with each affiliate’s age), and foundsimilar (insignificant) results as those reported in table 5.

25

Affiliate characteristics
We include two control variables at the affiliate level, consistent with the entry and exit theory of
Jovanovic (1982). Affiliate size (the logarithm of the number of employees of the affiliate in 1995 23 ) has
been found to be positively associated with firm survival (Dunne et al, 1989; Mitchell, 1994; Mata et al,1995). Studies have also shown that this positive relationship between firm size and survival applies toforeign affiliates (e.g. Mata and Portugal, 2000; Li, 1995). Affiliate age (the number of years the affiliate
has been in operation until 1995) is included to capture that newly established affiliates suffer more from“liability of newness”, while older affiliates have been able to improve their operations to adapt to hostcountry conditions. Earlier evidence supports a positive relationship between firm age and firm or affiliate
survival (e.g. Mitchell, 1994; Yamawaki, 1999; Benito, 1997; Shaver et al, 1997). On the other hand,
evidence has also been found for the presence of a “liability of adolescence” (Hannan, 1998), with theprobability of survival decreasing with age over a range of years (Mata and Portugal, 2002; Li, 1995). To
accommodate a more complex relationship between age and divestment, we include the quadratic term as
well as the linear term of affiliate age.
The entry mode of the affiliate is also likely to impact divestment probabilities. We include threedummy variables with wholly owned greenfield affiliates as reference group: majority owned JV (dummy
taking the value 1 if the affiliate is a joint venture in which the Japanese parent held a majority stake, 5195 percent), minority owned JV (dummy taking the value 1 if the affiliate is a joint venture in which theJapanese parent held a minority or 50 percent stake), and acquired affiliate (dummy taking the value 1 if
the affiliate was acquired by the Japanese parent).
The last affiliate characteristic is its market orientation. Multinational firms have different motives
for foreign affiliate establishments: they can use their foreign affiliates as a production base serving export
markets, or to manufacture products serving, and often adapting to, the local market. Export-oriented
affiliates established in Asia by Japanese electronic firms are often a vehicle to take advantage of thecomparative advantages in these countries in terms of manufacturing costs. They may be more sensitive to
23

The dataset does not include reliable sales figures for all affiliates.

26

changes in comparative advantages, and they tend to be less embedded in the local economy in terms ofsupplier and other linkages (Belderbos et al, 2001). Local-orient affiliates, in contrast, give more weight tolocal adaptation and are comparatively more integrated into local economy. Belderbos et al (2001) foundevidence that foreign affiliates of Japanese firms that are local market oriented demonstrate more intensive
backward linkages with local suppliers. Development of ties with local suppliers can be seen as countryspecific assets that increase local capabilities but loose their value once the firm decides to divest,
increasing exit costs (e.g. Song, 2002). Pan and Chi (1999) argue that local market oriented firms may
perform better since they are more shielded from fierce competition on world markets, but found noevidence in a sample of foreign owned affiliates in China. We include two market orientation variables:
Export orientation (dummy taking the value of 1 if all affiliate sales are on export markets), Mixed market
orientation (dummy taking value of 1 if the affiliate sells on both the local and export markets). Affiliatesthat are only selling on the domestic market serve as the reference group.

Country characteristics
The analysis controls for the potential impact of Japanese investor agglomeration in 1995 (thenumber of manufacturing affiliates in the electronics value chain in operation in the country in 1995,
excluding those affiliates belonging to the parent firm of the focal affiliate). With the measures of
responsiveness to Japanese and Keiretsu investor agglomeration controlling for the impact ofagglomeration at the time of entry and possible adverse selection, this measure of current agglomeration
can provide a more accurate estimate of relevant Japanese investor agglomeration externalities at the time
we study divestments. The current agglomeration measure may have a negative effect on the probabilityof divestment due to the beneficial effects of agglomeration, but this impact may be mitigated if
agglomeration is associated with increased competition (e.g. Chung and Kalnins, 2001). We also include ameasure of labor cost increase: the percentage growth in wages (expressed in dollars) for manufacturing
workers in the host country’s electronics industry between 1995 and 1998. In particular in an assembly
industry such as electronics, labor input is an important cost factor and labor cost is an important27

determinant of the relative attractiveness of a location (e.g. Belderbos and Carree, 2002; Song, 2002). A
third factor in location and divestment decisions is the growth of the local market. Market growth allows
manufacturing affiliates to grow without intensifying competition for market share, reducing the
likelihood of divestment (e.g. Li, 1995; Benito, 1997). We include as a measure of the growth in therelevant market, the percentage growth in the dollar value of the country’s electronics market between
1995 to 1998 (Electronics market growth). Finally, we include the average dollar value of annual inward
direct investment flows to the country between 1995 to 1998 (FDI inflow), as a broad measure of
attractiveness of the countries which should also pick up regulatory and other changes that impact theattractiveness of countries to FDI. 24
Summary statistics for the dependent variable, operational measures and control variables areprovided in table 4, and the correlation matrix is given in Appendix.

Insert Table 4

EMPIRICAL RESULTS

The results of the Probit model relating the probability of manufacturing affiliate divestment to
the operational measures and control variables are presented in the first column of table 5. The model ishighly significant as indicated by the Chi-square test statistic. The coefficient of country platform affiliate
has the expected sign (negative) but is not significant, which provides no support for Hypothesis 1. 25 The
coefficient of the size of country platform network is positive and significant for affiliates that are notcountry platform affiliates, as predicted by Hypothesis 2. In further confirmation of Hypotheses 2, size of
24

The number of country variables that can be included in the analysis is limited due to the fact that the analysis
covers a cross section of only nine Asian countries, causing multicollinearity in extended specifications. Adding
various other variables, such as GDP per capita growth or GDP growth, provide results similar to the electronics
demand growth factor.
25
We use conservative two-sided tests throughout.

28

country platform network has no significant impact for country platform affiliates. These results do
indicate a major distinction between platform and non-platform affiliates, but through a differential effectof network size, rather than a direct effect of country platform status. 26 . Hypotheses 3 and 4 are confirmedby the positive and significant coefficients of responsiveness to Japanese investor agglomeration at entry(at the 1 percent level) and responsiveness to Keiretsu investor agglomeration at entry (significant justbelow the 5 percent level. Affiliates for which the Keiretsu and Japanese agglomeration factor was ofgreater importance in determining the location decision were significantly less likely to survive in the
period of investigation (1995-1998), in support of the “adverse selection” argument.

Insert Table 5

Control variables
The estimated coefficients of the control variables are largely consistent with perceived theory andresults in previous empirical studies. Parent size is negative and significant, while both parent firm patentintensity and parent prior country experience has the expected negative sign but do not reach conventionalsignificance levels. Consistent with earlier studies, larger affiliates are less likely to be divested (thecoefficient of affiliate size is negative and significant at 10% level). Minority owned joint ventures, but
not majority owned joint ventures, have a greater probability of divestment than wholly owned greenfield
affiliates, consistent with the impact of equity stake on affiliate survival found in Dhanaraj and Beamish(2004). The coefficient for acquired affiliate is positive but not significant. 27 Divestment is related toaffiliate age in an inverted U-shape manner. The probability of divestment increases with age up to acertain point and then starts to decrease. These results are more in line with the view that age can be aliability due to organizational rigidity (e.g. Hannan, 1998) than with an organizational learning view.
26

One reason for this finding is that the combination of Hypotheses 1 and 2 require both a slope and a shift effect of
platform investment status, which leads to a relatively high degree of multicollinearity between the network size
variable for platforms and the platform dummy variable.
27
We note that the number of acquisitions is small in this sample of electronics investments in Asia. We identified
only five acquisitions, which does not allow to estimate the impact of this type of entry mode with precision.

29

Older affiliates may still rely on mature technologies or focus on markets with less growth potential, andin dynamic markets with rapid technological developments such as electronics, age is not necessarily an
advantage (Li, 1995). 28 The export orientation dummy has a positive sign, but the coefficient just does notreach conventional significance levels, while the mixed market orientation dummy is also positive but
insignificant.
Of the country variables Japanese agglomeration in 1995 has a negative sign and is highly
significant, indicating that the benefits of Japanese agglomeration dominate over potential competition
increasing effects, once the indirect impact through adverse selection is accounted for. Of the othercountry variables, labor cost increase has a positive and significant impact on divestment. The coefficientof electronics market growth, on the other hand, has a counter-intuitive positive sign but is not significant.
The same applies to the variable FDI inflow. Apparently, labor costs are the dominant consideration forlocation and survival of electronics plants in the Asian electronics industry. 29

Volatility and Uncertainty
As shown in the previous section, the systemic changes in macroeconomic circumstances in the
Asian region due to the Asian financial crisis during the period of investigation 1995-1998 led tosystematic uncertainty concerning future exchange rate changes, inflation, and economies’ capacity torecover. This systemic uncertainty related to a regional shock such as the Asian financial crisis is lesslikely to be well reflected in conventional measures of uncertainty such as coefficients of variation in
exchange rates. Nevertheless, the figures on the nine Asian countries suggest that there were importantdifferences in macroeconomic developments, in particular real exchange rate movements and volatility.
28

The coefficients indicate that for the larger majority of affiliates, the probability of divestment increases with age,as the turning point is only reached at 35 years. We note, however, that caution should be exercised in interpretingthese coefficients, as the findings may be influenced by left censoring in our sample.
29
Complicating the estimation of the impacts of labour cost and demand increases are the exchange rate changes(depreciations and devaluations) for several Asian countries during the period, which reduced both labour costs andmarket demand in dollar terms, and introduce a positive correlation between the two variables. We could also expectthat export oriented firms are more sensitive to changes in labor cost than domestic market oriented firms. Indeed, atest including the interaction effect of exporting affiliates and labor cost growth produced a significantly positivecoefficient. Interacting domestic market orientation with market growth resulted in the expected negative sign but theinteraction effect was not significant.

30

Following earlier work on foreign investment and real options (e.g. Kouvelis et al, 2001), we took thevariation in the monthly real exchange rate index (local currency to Yen, 1995-1998) as an imperfectmeasure of country-specific uncertainty. We grouped the countries into low volatility and high volatility
countries, as the data suggested a relatively clear distinction here. 30 In an extended model we tested the
hypotheses that country platform affiliates are less likely to be divested in high volatility countries, andthat for platform investments in high volatility countries there is an even stronger mitigated impact of
network size. We include the country platform affiliate dummy and the size of country platform network
variable separately for high and low volatility countries. The empirical results are reported in the second
column of table 5. Platform affiliate status has a negative and significant impact on divestment for highvolatility countries, but not for low volatility ones. High or low volatility does not matter for the impact ofcountry platform network size: both terms are insignificant, while the impact for non-country platforms
remains robustly positive and significant. These results provide further evidence of the significance of thereal options and network flexibility explanation of foreign affiliate divestments.

CONCLUSIONS AND DISCUSSION

We analyzed divestment decisions in a comprehensive sample of 1078 Japanese electronics
manufacturing affiliates in operation in 1995 in nine Asian countries during the years leading up and into
the Asian financial crisis (1995-1998). The empirical results gave broad support for a real options
perspective on divestments, as well as for the notion that foreign investor agglomeration leads to ‘adverse
selection’ by attracting weakly competitive firms.

30Interacting the exchange rate volatility measure as such with the platform dummy produced an expected negative,
but insignificant effect, suggesting that the moderating impact of volatility is not well captured by a linear
relationship. We also added a separate interaction term for the highest volatility country (Indonesia) with theplatform dummy: this term similarly was negative but not significant. Other results remained robust.

31

Affiliates with ‘country platform’ status, i.e. those affiliates that are the sole manufacturing
presence of a firm in a country, were less likely to be divested if located in countries characterized by higheconomic uncertainty as indicated by real exchange rate volatility. Affiliates that did not have country
platform status (they were one among multiple manufacturing affiliates operated by the firm in the country)
had greater odds of divestment if the parent firm operated a larger network of manufacturing platforms in
different Asian countries, and so could exercise broader relocation and flexibility options in response todifferential macroeconomic developments. The results are consistent with the notion that a network of
manufacturing plants provides option value to the firm, by providing the flexibility to adjust the
distribution of manufacturing operations over locations under conditions of uncertainty concerning
exchange rates, labor cost, and market conditions (Kogut and Kulatilaka, 1994a; Pennings andSleuwaegen, 2000). The findings provide evidence that multinational firms both maintain flexibility
options through operating a multinational plant network of platform affiliates in multiple Asian countries,and exercise this flexibility option through divestments and relocations of manufacturing activities that do
not provide additional flexibility value. The results suggest that affiliate divestment decisions should beconsidered in the context of wider multinational firm strategy and their position in international plant
networks, rather than as separate decisions, as has been the approach in most previous work on foreigndivestments.
The role of foreign investor agglomeration in affiliate divestment is a complex one, and we
attempted to bring more clarity in this relationship by investigating the potential impact of agglomeration
through the process of ‘adverse selection’: the notion that the most competitive firms are less attracted toagglomerated areas as they are more likely to contribute to agglomeration externalities benefiting
competing firms, rather than benefiting from such externalities themselves. Earlier studies provided strong
confirmation that Japanese investor agglomeration attracts further Japanese investments, a pattern that isparticularly visible for member firms in vertical business groups (keiretsu). We used a two-stepmethodology to analyze the impact of adverse selection, examining the determinants of location choice atthe time entry of the affiliates with a first-step conditional logit model. From this model we could derive32direct indicators of potential adverse selection due to Japanese and vertical business group agglomeration
at entry as the elasticity of the location choice probability with respect to agglomeration at entry measures.
The results of the conditional logit analysis replicated earlier findings in the location and agglomeration
literature of a major impact of Japanese and keiretsu agglomeration on location choice. The analysis also
confirmed a substantial firm heterogeneity in the response to agglomeration depending on investor
characteristics. Larger firms were less attracted to agglomerations, while vertical keiretsu member firms,
but not leading core firms of the group, were attracted to Keiretsu agglomeration. The divestment analysis
confirmed that those affiliates of which the location choice at entry was more responsive to Japanese andKeiretsu agglomeration, were more likely to be divested, suggested that adverse selection indeed plays arole in divestment patterns among Japanese firms.
The divestment analysis at the same time showed that affiliates operating in 1995 in countries witha substantial Japanese affiliate presence were less likely to be divested. This positive impact on survival of
current Japanese investor agglomeration is consistent with the presence of important Japanese firm
agglomeration externalities (e.g. Belderbos and Carree, 2002; Head et al, 1995). The positive impact
contrasts with earlier results (e.g. Shaver and Flyer, 2000; Kim and Delios, 2003), where a negative
impact of Japanese investor agglomeration on firm survival was found and subsequently attributed to ahigher intensity of competition associated with this agglomeration. Our results suggest that the paradox
between a strong attraction of agglomerated areas to foreign investors and the largely negative impact ofagglomeration on firm survival found in previous empirical work may well be due to a failure to control
for adverse selection effects. In our study, by exploring firm heterogeneity in the response to
agglomeration and by distinguishing agglomeration at the year of entry from agglomeration during theperiod in which divestments are examined, we could distinguish the adverse selection effect associatedwith agglomeration from the direct impact of agglomeration. After controlling for the impact of adverse
selection, an indicator of agglomeration is likely to bring out the real net effect of agglomeration

33

externalities and increased competition. 31 In this regard, our approach and results echo the findings in
Shaver (1998) that one has to control for endogeneity of strategic choices of firms in analyzing the impactof these choices on firm performance. Location strategy as it is influenced by agglomeration, is dependent
on the firms’ competitive resources. Failure to control for this endogeneity of location choice may
incorrectly attribute divestment to a direct (competition) impact of agglomeration, rather than to theunderlying firm characteristics that governed the location choice.
Our findings on the contrasting impact of Keiretsu agglomeration for core firms and members firms
are in line with those obtained by Kim et al. (2004), to the extent that the most powerful members ofkeiretsu (cf. the core firms) distinguish themselves by pursuing independent location strategies to increase
geographic scope. The results contribute to the discussion concerning the efficiency and performanceenhancing or competition reducing impact of horizontal and vertical Keiretsu (e.g. Miwa and Ramseyer,2002). Hundley and Jacobsen (1998) found mixed export performance effects of keiretsu membership, andsuggested that preferential intra-group trading may shield firms from competitive pressures, reducing
performance. Weinstein and Yafeh (1995) found keiretsu firms to engage in overinvestment financed by
the main bank, which led to significantly reduced profitability of Keiretsu firms compared to independent
firms. Our results similarly suggest that vertical Keiretsu presence in foreign countries, although it canallow for transfer of efficient Japanese business practices such as just-in-time delivery systems and quality
control (e.g. Martin et al. 1995; 1998; Smith and Florida, 1994), also involves ‘overinvestment’ by weaklycompetitive member firms that have lower survival chances in the longer term.
Our results reconfirm the need for countries to attract major investors in order to generate
agglomeration benefits sustaining incoming investments flows, but suggest a qualification. Investment
agglomeration also attracts lower quality investments that are associated with higher divestment and31

However, we note that differences in results of the present and earlier studies may be partly due to the scope of theindustry cluster under consideration, since our definition of the broad electronics industry included material andcomponent suppliers as well as final goods manufacturers. Hence, the direct competition effect of ‘like’ firms
competing in the same market segment is likely to be of less importance compared with the benefits ofagglomeration such as the provision of specialized high quality inputs, information spillovers, and the availability ofskilled labor (c.f. Chung and Kalnins, 2001).

34

turbulence in agglomerated areas. Another policy implication is that containing labor cost increases may
be an important means to avoid foreign divestment and relocations. The depreciation of Asian currencies
with the Asian financial crisis was associated with substantial declines in real wage costs in several
ASEAN countries, and our results suggest that the crisis has led multinational firms to maintain, rather
than divest, manufacturing operations.

Limitations and Further Research
A limitation of this study is the restriction of our sample to Japanese affiliates in the (broadly
defined) electronics sector in Asia, which reduces the scope for generalizations. The existence ofextensive plant networks by multinational firms in different countries, the importance of labor costs, andthe ‘footloose’ nature of electronics assembly plants, are to an extent particular to assembly industries
such as the electronics industry. The role of vertical industrial groups and suppliers networks isparticularly important in the industrial organization of Japanese firms. Hence, it would be of interest toinvestigate to what extent similar systematic patterns of divestment occur in other industries and foraffiliates owned by multinationals based in other countries. An interesting setting would be foreigndivestment by South Korean firms, where agglomeration and group affiliation have similarly been foundto impact investment decisions (e.g. Park and Chang, 1995). Second, our analysis of divestment only
covered a time span of 4 years. This was a proper setting for our analysis, as this was a period of major
uncertainty concerning exchange rate changes and market performance in Asia, during which divestments
and relocation became a common phenomenon. A longitudinal analysis of affiliates' survival probabilities
by extending the time period of analysis would however have important benefits. It would allow use ofsurvival models to investigate the dynamic impact of agglomeration and plant networks on divestment,
and would introduce spell variation in the dependent variable and time variation in the covariates. 32 An
extension of the analysis would also provide further insights into the reaction of multinational firms to the32

Unfortunately, the Research Institute of Electronics Industry has ceased publishing the Asian affiliate data books
and replaced this with a volume focusing on affiliates in China only, complicating an extension of the current
analysis.

35

Asian financial crisis and its aftermath, and could allow derivation of time-variant country-specificuncertainty indicators impacting the option value of country platforms (cf. Kouvelis et al. 2001, Pennings
and Sleuwaegen, 2000).
Another avenue for future research is to analyze the impact of agglomeration economies andcompetition effects in more detail. A possible improvement of the analysis would be to estimate theimpact of agglomeration at the level of regions rather than countries. This will allow for more accurate
measurement of relevant agglomeration and labor costs at the regional level, which is of importance inparticular for the growing number of affiliates established in the various regions of China. 33 Further
insights could also be obtained by differentiation of the type of agglomerated establishments (e.g. Chungand Kalnins, 2001) with an expected diverging impact on affiliate survival. There may be differences
between affiliates established by firms with the same country of origin, affiliates under other foreign
ownership, and domestic firms. Agglomeration economies should dominate competition effects foraffiliates further in the value chain but not for directly competing firms. In the context of the electronics
industry, a first distinction could be made between component suppliers and final goods producers. Theseissues suggest an extensive agenda for future research.

Acknowledgements

Rene Belderbos gratefully acknowledges the hospitality and financial support from the
Global Security Research Institute at Keio University, where he was a visiting fellow during
July-August 2005. his paper benefited from helpful comments by two anonymous referees, Leo
Sleuwaegen, Reinhilde Veugelers, Koen De Backer, Ryuhei Wakasugi and participants at the
Korea and World Economy Conference in Seoul (2004), the Ninth International Convention of33

We performed a rough test of the impact of regional location in China by including dummies for location,
distinguishing the South (with Guangdong a dominant province), East (Shanghai) and North (Beijing). We found no
significant impact of these location dummies, with other results left unchanged.

36

the East Asian Economic Association in Hong Kong (2004), the Annual conference on Corporate
Strategy at WHU-Vallendar (2005), the Annual conference of the Academy of International
Business (AIB) in Quebec (2005), and seminars at the Katholieke Universiteit Leuven and Keio
University.

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Table 1: Distribution by country of overseas plants and divestment
Host countries

Manufacturing affiliates in 1995

or regions
NumberShare in total

Divested affiliates:% divested

1995 - early 1999

affiliates

NumberShare in total(row%)

%

%
China

237

21.99%

16

16.49%

6.75%

Hong Kong

45

4.17%

7

7.22%

15.56%

Indonesia

58

5.38%

2

2.06%

3.45%

Korea

98

9.09%

14

14.43%

14.29%

Malaysia

228

21.15%

11

11.34%

4.82%

Philippines

35

3.25%

3

3.09%

8.57%

Singapore126

11.69%

24

24.74%

19.05%

Thailand108

10.02%

2

2.06%

1.85%

Taiwan143

13.27%

18

18.56%

12.59%

Total

1078

100%

97

100%

9.00%

46

Table 2: Heterogeneous responses to the crisis and macroeconomic developments (1995-1998)

Major indicators

CH

HK

ID

MA

PH

SG

KR

TH

TW

Labor cost growth(current prices, in
USD)

38.2% 30.0% -63.3%

19.4% -31.9%

12.4% -30.8% -51.3% -11.3%

Real GDP growth(local currency)

30.7% 4.6%

13.6%

11.7%

15.5%

15.0%

9.3%

-7.1%

21.7%

Consumer priceincrease

4.3% 12.2%

96.7%

15.7%

24.3%

0.3%

12.1%

17.6%

5.7%

Change in nominal
exchange rate against
Yen

15.7% 14.8% -65.4% -23.2% -22.5%-1.7% -27.0% -20.2%

-3.0%

23.7

22.2

Exchange rate
volatility: (variance inindex of monthly realexchange rate against
Yen)

68.7

93.0

3528.6

164.6

90.8

339.7

215.6

Notes: CH=China; HK=Hong Kong; ID=Indonesia; MA=Malaysia; PH=Philippines; SG=Singapore;
KR=Korea;TH=Thailand; TW=Taiwan; Data sources: UNIDO, ILO, IMF, World Bank.

47

Table 3: Conditional logit Estimates of affiliate Location Choice Model
Japanese investor agglomeration at entry

0.0071[0.0023]***

Japanese investor agglomeration at entry * parent size at entry-0.0009[0.0003]***

Keiretsu investor agglomeration at entry (member firms)

0.0561[0.0204]***

Keiretsu investor agglomeration at entry (core firms)

0.0446[0.0449]

FDI inflow at entry

0.5067[0.0447]***

Hong Kong-1.6361[0.1662]***Indonesia-0.8067[0.1659]***Korea-0.1503[0.1631]

Malaysia

0.0451[0.1288]

Philippines-0.9187[0.2085]***Singapore-0.7635[0.1334]***Thailand-0.2666[0.1459]*

Taiwan0.0188[0.1778]Chi Square
Pseudo-R2
Log likelihood
Number of choices
Number of choice observations

602.04***0.1271-2067.6
91078

Notes: *, **, *** indicate significant at the 10, 5, 1 percent level, respectively (two-tailed test);
standard errors in parentheses. PR China is the reference location.

48

Table 4: Descriptive statistics of dependent and explanatory variables
Name

Divestment
Country platform
affiliate
Size of country
platform network
Responsiveness toJapanese investor
agglomeration at
entry
Responsiveness to
Keiretsu investor
agglomeration at
entry
Parent firm Patentintensity
Parent size
Parent priorcountry experience
Affiliate size
Affiliate age
Majority owned JVMinority owned JV
Acquired affiliate
Export orientation
Mixed market
orientation
Japanese investor
agglomeration in
1995
Labor cost increase

Description

Hypothesis:
sign

Mean

Stdev

0.09

0.29

0.55

0.50

H1: -

2.92

2.40

H2: +

the elasticity of the location choice probability withrespect to Japanese investor agglomeration at entry(calculated from the location choice model)

0.07

0.18

H3: +

the elasticity of the location choice probability withrespect to Keiretsu investor agglomeration at entry(calculated from the location choice model)

0.05

0.11

H4: +

0.89

1.50

11.13

2.36

0.82

1.78

5.65

1.41

8.92

8.04

0.24

0.43

0.30

0.46

0.00

0.07

0.27

0.44

0.48

0.50

202.27

86.81

0.01

0.33

binary variable denoting if the affiliate is divested or not
between early 1995 and early 1999
dummy taking the value 1 if the affiliate is the only
manufacturing affiliate of its parent in the country in 1995
the number of countries in which the parent firm has
manufacturing operations in 1995 (other than then the
country of the focal affiliate)

Number of US patents granted to the parent firm during
1993-1999 times 1000, divided by parent sales in 1995
the logarithm of parent firm sales (million Yen) in 1995
the number of manufacturing affiliates established by theparent firm in the country prior to the entry of the focal
affiliate.
the logarithm of the number of employees of the affiliate
in 1995
the number of years the affiliate has been in operation
until 1995
dummy taking the value 1 if the affiliate is a joint venturein which the Japanese parent holds a majority stake (51 95 percent)dummy taking the value 1 if the affiliate is a joint venturein which the Japanese parent holds a minority or 50
percent stakedummy taking the value 1 if the affiliate was acquired by
the parent firm
dummy variable taking the value of 1 if all affiliate sales
are on export markets
dummy variable taking value of 1 if the affiliate sells on
both the local and export markets
the number of Japanese manufacturing affiliates in theelectronics value chain in operation in the country in
1995, excluding those affiliates belonging to the parent
firm of the focal affiliate
the percentage growth in annual wages (expressed indollars) for manufacturing workers in the host country’s
electronics industry between 1995 and 1998

Electronics Market
growththe percentage growth in the dollar value of the country’s
electronics market between 1995 to 1998

0.08

0.37

FDI inflow

average yearly annual inward direct investment flows to
the country between 1995 to 1998 in billion dollars

13.28

15.76

49

Table 5: Probit estimates of Japanese manufacturing divestment in Asia 1995-1998
Model I

Model II

-0.2826[0.2032]

Country platform affiliate

Country platform affiliate (high volatility countries)-0.7016[0.2748]**

Country platform affiliate (low volatility countries)-0.0452[0.2257]

Country platform network size (non-platform affiliates)

0.1049[0.0500]**

Country platform network size (platform affiliates)

0.0607[0.0568]

0.1056[0.0491]**

Country platform network size
(platform affiliates in high volatility countries)

0.1149[0.0885]

Country platform network Size
(platform affiliates in low volatility countries)

0.0333[0.0696]

Responsiveness to Japanese investor agglomeration at entry

1.2454[0.6496]*

1.2129[0.6425]*

Responsiveness to Keiretsu investor agglomeration at entry

1.2997[0.4957]***1.249[0.5125]**

Parent firm patent intensity-0.0531[0.0415]-0.0612[0.0430]

Parent size

-0.1182[0.0588]**-0.1208[0.0571]**

Parent prior country experience-0.0577[0.0537]-0.0615[0.0574]

Affiliate size

-0.0806[0.0492]*-0.0666[0.0513]Affiliate age

0.0798[0.0326]**

0.0682[0.0333]**

Affiliate age (squared)-0.0023[0.0011]**-0.0021[0.0011]*50

Table 5: Probit estimates of Japanese manufacturing divestment in Asia 1995-1998 (continued)
Model I

Model II

Minority owned JV

0.3566[0.1399]**

0.3684[0.1417]***

Majority owned JV-0.1031[0.1702]-0.1031[0.1711]

Acquired affiliate

0.6608[0.6294]

0.6851[0.6629]

Export orientation

0.2678[0.1749]

0.2617[0.1748]

Mixed market orientation

0.1194[0.1499]

0.0937[0.1498]

Japanese investor agglomeration in 1995

-0.004[0.0012]***-0.003[0.0013]**

Labor cost increase

0.6756[0.2952]**

0.4259[0.2884]

Electronics Market growth0.1437[0.3206]-0.2838[0.3699]

FDI inflows

0.0065[0.0097]

0.0093[0.0096]

Constant

0.1822[0.7007]0.0416[0.7041]

Pseudo R2
Number of observations
Chi Square
Log likelihood

0.145
1078
89.28***-278.70.155
1078
96.49***-275.5

Notes: *, **, *** indicate significant at the 10, 5, 1 percent level, respectively (two-tailed test); Huber-WhiteSandwich robust standard errors in parentheses. Wholly owned Greenfield and local market orientation are thereferences groups.

51

Appendix: Correlation matrix

1
1

Divestment
Country platform
affiliate
Size of country platform
network
Responsiveness toJapanese investor
agglomeration at entry
Responsiveness to
Keiretsu investor
agglomeration at entry
Parent firm Patentintensity

1.00

Parent size
Parent prior country
experience

9
10
11

2

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

-0.02

1.00

-0.05

-0.51

1.00

0.17

0.37

-0.58

1.00

0.02

-0.06

0.00

-0.18

1.00

-0.08

-0.15

0.31

-0.32

-0.09

1.00

-0.16

-0.49

0.76

-0.81

0.16

0.38

1.00

-0.05

-0.41

0.43

-0.39

0.19

0.09

0.41

1.00

Affiliate size

-0.11

-0.23

0.38

-0.39

-0.04

0.18

0.42

0.07

1.00

Affiliate age

0.04

0.01

0.18

-0.16

-0.19

0.05

0.13

-0.21

0.27

1.00

Majority owned JV

-0.07

-0.03

-0.02

-0.04

0.08

-0.05

0.03

0.03

0.00

-0.03

1.00

12

Minority owned JV

0.12

-0.08

0.05

0.01

0.02

-0.06

0.00

0.07

-0.11

0.06

-0.38

1.00

13

Acquired affiliate

0.03

0.01

0.03

-0.01

-0.02

0.02

0.03

-0.01

0.02

0.04

-0.04

-0.04

1.00

14

-0.02

-0.02

0.03

-0.09

-0.07

0.10

0.11

-0.02

0.24

-0.02

-0.05

-0.17

-0.01

1.00

15

Export orientation
Mixed market
orientation

0.02

0.12

-0.11

0.09

-0.02

-0.11

-0.16

-0.15

0.01

0.13

-0.03

0.01

-0.01

-0.58

1.00

16

Japanese investor
agglomeration in 1995

-0.07

-0.18

-0.03

0.03

0.10

-0.03

0.01

0.18

-0.03

-0.38

0.06

-0.01

0.01

-0.06

-0.01

1.00

3

4

5
6
7
8

17

17

18

0.02

-0.12

-0.04

0.05

0.05

0.00

-0.05

0.14

-0.11

-0.21

-0.01

-0.08

0.02

-0.03

0.00

0.77

1.00

18

Labor cost increase
Electronics Market
growth

-0.03

-0.15

0.02

-0.09

0.04

0.04

0.04

0.15

-0.10

-0.32

0.10

0.00

0.01

-0.01

-0.06

0.66

0.60

1.00

19

FDI inflows

-0.03

-0.16

0.01

-0.07

0.06

0.01

0.02

0.20

-0.12

-0.42

0.10

0.04

0.00

-0.04

-0.08

0.77

0.67

0.87

53

19

1