which country matters? institutional development … · institutional development on foreign...

Strategic Management JournalStrat. Mgmt. J., 29: 1179–1205 (2008)

Published online in Wiley InterScience (www.interscience.wiley.com) DOI: 10.1002/smj.705

Received 1 March 2005; Final revision received 31 March 2008

WHICH COUNTRY MATTERS? INSTITUTIONALDEVELOPMENT AND FOREIGN AFFILIATEPERFORMANCE

CHRISTINE M. CHAN,1 TAKEHIKO ISOBE,2 and SHIGE MAKINO3*1 School of Business, The University of Hong Kong, Pokfulam, Hong Kong2 Graduate School of Business Administration, Keio University, Yokohama, Japan3 Department of Management, The Chinese University of Hong Kong, Shatin, N.T.,Hong Kong

This article investigates the effect of the level of institutional development of host countries onthe level of and variation in foreign affiliate performance. Institutional development is defined asthe extent to which the economic, political, and social institutions in a host country are developedand are favorable for foreign affiliates. A longitudinal analysis of over 30,000 foreign affiliate-year cases that include 6,985 foreign affiliates in 38 host countries between 1996 and 2001shows that foreign affiliate performance varies noticeably both across and within host countries.The results suggest that the level of institutional development, as determined by the InstitutionalDevelopment Index (IDI), a new measurement developed in this study, has a strong negativecurvilinear relationship with the variation in foreign affiliate performance and a negative effecton the level of foreign affiliate performance. The implications for future research, practice, andpolicymaking are discussed. Copyright 2008 John Wiley & Sons, Ltd.

INTRODUCTION

Firm performance is an important issue in strategicand international management. Previous researchhas drawn on the industrial organization economicsperspective and the resource-based view of thefirm to suggest that industry structure and a firm’sresources and capabilities are the primary deter-minants of firm performance. In an extension ofthis area of research, scholars have examined theextent to which the differences between industries,firms, and business units explain the variation inthe performance of business units in a country(McGahan and Porter, 1997; Rumelt, 1991). While

Keywords: institution-based view of foreign affiliate per-formance; institutional development index; emergingeconomies; legitimacy and competition; risk and returnin foreign direct investment; strategic choice under uncer-tainty*Correspondence to: Shige Makino, Department of Manage-ment, Chinese University of Hong Kong, Shatin, N.T., HongKong. E-mail: [email protected]

acknowledging the importance of the differencesbetween industries and firms, more recent studiesexplore the extent to which differences betweencountries explain the variation in the performanceof the foreign affiliates of multinational corpora-tions (MNCs) in multiple countries (Christmann,Day, and Yip, 1999; Makino, Isobe, and Chan,2004). Although these studies suggest that countrydifferences do matter, they focus on the relativeimportance of country effects in relation to indus-try and firm effects. Little has been revealed aboutthe countries in which the variation in foreign affil-iate performance is greater (or lesser), or aboutthe host country-specific factors that influence thisvariation.

Several previous studies examine the country-specific influences on the business activities andperformance level of MNCs. One group of thesestudies focuses on the comparative advantages ofhost countries, which derive from differences inthe availability of ‘naturally inherited’ factors of

Copyright 2008 John Wiley & Sons, Ltd.

1180 C. M. Chan, T. Isobe, and S. Makino

production (e.g., labor, land, and capital) (Dunning,1980, 1988, 1993), and examines why MNCschoose to locate their subsidiaries in one coun-try over another to improve their productivity.Another group of studies focuses on the competi-tive advantages of home countries, which derivefrom the differences in ‘created’ capabilities—especially those that develop and upgrade inno-vation and technology—among home countries(Porter, 1990), and examines why, in a givenindustry, MNCs that originate from a particularhome country outperform those originating in othercountries. Yet another group of studies focuses onthe interplay between the competitive advantagesof MNCs and the comparative advantages of hostcountries (Kogut, 1985; Ghemawat, 2003), andexplains how MNCs can gain from exploiting thesimilarities (aggregation) and differences amongcountries (arbitrage) (Ghemawat, 2003). Althoughthe performance level of MNCs and their foreignaffiliates is influenced by the availability of thedirect inputs of production and their capability toharness both aggregation- and arbitrage-orientedactivities, it is also affected by contextual factorssuch as host country institutions, because foreignfirms cannot be immune to the institutional con-text of the host country in which they are embed-ded (Ghemawat, 2001; Kostova and Zaheer, 1999;Peng, 2002; Westney, 1993).

Other previous studies of MNCs examine theinstitutional environments of the host countries inwhich foreign affiliates operate (Henisz, 2000b;Kostova and Zaheer, 1999; Miller and Eden, 2006;Rosenzweig and Singh, 1991; Westney, 1993;Zaheer, 1995). Most of these studies examine thedistance between the institutional environments ofthe home country and those of the host country,rather than on the institutional distance among dif-ferent host countries, despite the fact that the extentto which institutional environments are developedvaries from one host country to another. As eachhost country has its own economic, political, andsocial institutions that affect national economicgrowth (Barro, 1991; Hall and Jones, 1999; Knackand Keefer, 1997; Krueger and Lindahl, 2001;La Porta et al., 1997; North, 1990; Olson, 1996;Williamson, 1985) and the profitability of engag-ing in business activities (Khanna and Rivkin,2001; North, 1990), research is needed to exam-ine how the level of institutional development ofthe host country influences the performance of for-eign affiliates in the country and the extent of this

influence. Identifying this influence is of strate-gic importance to MNCs, because they need tomanage local institutional contexts when expand-ing into foreign countries to maximize the returnon and minimize the risk of their investment.

In an extension of previous studies, our studyaims to examine the influence of the level ofinstitutional development on foreign affiliate per-formance from the neo-institutional perspective(North, 1990; Scott, 1995). We define the levelof institutional development as the extent to whichthe economic, political, and social institutions ina host country are developed and are favorable toforeign affiliates. We focus on two types of foreignaffiliate performance: the level of foreign affiliateperformance, and the variation in foreign affiliateperformance within a host country. The level offoreign affiliate performance represents the ‘return’on an investment, and indicates the profitabilityof foreign affiliates in a host country. The varia-tion in foreign affiliate performance within a hostcountry represents the ‘risk’ of an investment, andindicates the extent to which the performance offoreign affiliates in a host country deviates fromthe host country mean. Using these performancemeasures, our study examines how foreign affiliateperformance varies both between and within hostcountries. We argue that the level of foreign affil-iate performance varies across countries becausehost countries differ in the development of theirinstitutions, which affects the efficiency of markettransactions and transformation. We also argue thatforeign affiliate performance varies within a hostcountry because foreign affiliates differ both in thestrategic actions that they take in response to thelevel of development of the host country institu-tions and in their ability to manage the institutionalidiosyncrasies of the host country.

Our study differs from previous work in threeways. First, it takes an institution-based viewof foreign affiliate performance. Although previ-ous studies that draw on the industrial organiza-tion economics perspective and the resource-basedview of the firm (Barney, 1991; Porter, 1980;Wernerfelt, 1984) contribute to our understandingof firm performance, the drivers of firm perfor-mance are not limited to the structural character-istics of industries and firm-specific resources andcapabilities. As the foreign affiliates of MNCs areembedded in the institutional environment of hostcountries, which have different sources of author-ity and different sets of institutional arrangements

Copyright 2008 John Wiley & Sons, Ltd. Strat. Mgmt. J., 29: 1179–1205 (2008)DOI: 10.1002/smj

Which Country Matters? 1181

(Ghoshal and Westney, 1993; Kostova and Zaheer,1999; Sundaram and Black, 1992), an analysis ofthe influence of host country institutions shouldprovide an additional perspective on the drivers offoreign affiliate performance.

The second distinction of this study is that itexamines the influence of the level of institutionaldevelopment on foreign affiliate performance. Pre-vious studies show that country effects, in additionto industry and firm effects, are the main sourcesof performance differences among foreign affili-ates (Christmann et al., 1999; Makino et al., 2004).However, these studies do not explain whether hostcountries exert different levels of influence on thelevel of and variation in foreign affiliate perfor-mance at different stages of institutional develop-ment.

Third, unlike most previous studies that examinethe effect of a single dimension of country-specificattributes on economic performance, this studyexplores the influence of the institutional devel-opment of a host country on foreign affiliate per-formance as measured by 12 national institutionalcharacteristics that capture the economic, political,and social aspects of the institutional environment.

In the next section, we briefly review the lit-erature that provides the theoretical and empiri-cal foundations of work on the influence of eco-nomic, political, and social institutions on firm(foreign affiliate) performance, and generate a setof hypotheses that specify the influences of insti-tutional development on the level of and variationin foreign affiliate performance. To examine thesehypotheses, we use a sample of more than 30,000foreign affiliate-year cases, which include 6,985foreign affiliates that were established by 1,421Japanese MNCs in 38 countries across 169 indus-tries (three- to four-digit standard industrial classi-fication [SIC] codes) between 1996 and 2001. Thearticle concludes by discussing the implications ofthe findings for MNCs, policymakers, and furthertheoretical development.

LITERATURE REVIEW

North defines institutions as ‘the humanly devisedconstraints that shape human interaction’ (North,1990: 3), whereas Scott defines them as ‘cognitive,normative, and regulative structures and activitiesthat provide stability and meaning to social behav-ior’ (Scott, 1995: 33). Both theorists contend that

institutions constitute the rules of the game, bothformal (such as regulations and laws) and infor-mal (such as codes of conduct and norms), thatstructure the economic, political, and social rela-tionships in a society or country (North, 1990;Scott, 1995). It is economic, political, and socialinstitutions, along with technology, that determinetransaction costs and the transformation costs ofproduction, and thus the profitability of engagingin business activities in a country (Khanna andRivkin, 2001; North, 1990).

Economic institutions, which generally involvemarket intermediaries, determine the incentivesfor and constraints on economic actions (North,1990). Market intermediaries include agents suchas investment bankers, auditors, solicitors, con-sultants, brokers, traders, and dealers. Interme-diary institutions credibly communicate informa-tion between transaction parties (i.e., sellers, con-sumers, investors, and creditors), and serve toresolve information problems and reduce trans-action costs in the product, capital, and financialmarkets (Akerlof, 1970; Diamond, 1984; Khannaand Palepu, 1997, 2000a; Khanna and Rivkin,2001). When both the availability of and accessto credible intermediaries are insufficient (Khannaand Palepu, 1997, 2000a), firms find it costly toraise funds, to acquire the necessary inputs, andto find qualified professional intermediary services(Khanna and Palepu, 2000b).

Economic institutions also involve the suppli-ers of the infrastructure that supports economictransactions. This supporting infrastructure takesthree forms: physical, human, and technological.Physical infrastructure involves the basic facil-ities, services, and installations needed for thelocal economy to function. Human infrastructureinvolves skilled labor and the social or profes-sional networks through which firms acquire newknowledge (Saxenian, 1994; Teece, 1986). Techno-logical infrastructure involves what Porter (1990)calls the ‘home base’ for technology development,from which firms carve their competitive advan-tage in a particular industry. These three types ofsupporting infrastructure generate efficiency in theoperations, knowledge acquisition, and technolog-ical development of firms.

Political institutions include governments andthe constraints that they impose on key actors,such as politicians and political parties. Politicalinstitutions determine policies in such areas astax rates and tariffs (Casson, 1982; Grubert and



Mutti, 1991), investment regulations (Contractor,1990; Djankov et al., 2002), restrictions on foreignownership (Gomes-Casseres, 1990), governmentprotection (Boddewyn and Brewer, 1994; Salo-rio, 1993), and foreign exchange controls (Cas-son, 1982). Some host-country policies impede theprofit opportunities of foreign operations. Someexamples of such policies are local governmentsraising the entry barriers (Bergara, Henisz, andSpiller, 1998), providing indigenous rivals withfavorable regulation and procurement conditions(Contractor, 1990; Fagre and Wells, 1982; Lecraw,1984), opportunistically expropriating the assets offoreign operations (Henisz, 2000b), and changingtrading agreements and investment regulations topenalize foreign operations (Bergara et al., 1998;Henisz and Zelner, 2005). However, some localgovernments attract foreign direct investment byoffering investment incentives, such as protectionagainst investment risk and permission to tradeand invest, or by ensuring a competitive advan-tage, such as through government purchases andmonopolies, over local rivals in return for botheconomic and noneconomic contributions (Bod-dewyn and Brewer, 1994).

Political institutions also set and enforce the ruleof law (Rodriguez, Uhlenbruck, and Eden, 2005).The lack of transparency of laws or their inad-equate enforcement both result in the inadequateprotection of intellectual property rights (Oster-gard, 2000; Oxley, 1999) and widespread cor-ruption (Habib and Zurawicki, 2002; Kaufmannand Wei, 1999; Tanzi, 1998). Poor protection ofproperty rights discourages firms from pursuinginnovation and thus from operating competitively(North, 1990). The spread of corruption may createopportunities for foreign firms to engage in polit-ical behavior (Boddewyn, 1988; Boddewyn andBrewer, 1994), but can also threaten their abilityto gain fair rents from their operations, as theyare obliged to waste their resources on unproduc-tive behavior (Kaufmann and Wei, 1999). Indeed,corruption is considered to be a more costly taxon economic activities than legal taxes (Habib andZurawicki, 2002; Shleifer and Vishny, 1993).

Social institutions derive from the members ofa population associating and interacting exten-sively with one another to develop recursive prac-tices (Berger and Luckmann, 1966; Giddens, 1984;March and Olsen, 1989; Scott, 1995; Searle, 1995).Social institutions have their own distinct practicesthat constrain the choice of action and facilitate

acceptable and preferred behavior by the membersof a society (Martin, 2004). As these practices dif-ferentiate one institution from another, social insti-tutions make a difference to work ethics (Weber,1930), attitudes toward work (Hofstede, 1980),trust (Fukuyama, 1995; La Porta et al., 1997),democracy (Putnam, 1993), beliefs about the basisof productivity (Porter, 2000), productive capac-ity (DiMaggio, 1994), and management dynamics(Franke, Hofstede, and Bond, 1991), which in turninfluence the costs of engaging in business activ-ities in a country. For example, a high degree oftrust among the members of a society is found tobe associated with a high level of economic per-formance (Fukuyama, 1995; La Porta et al., 1997;Putnam, 1993), because trust enables people toavoid engaging in inefficient noncooperative traps(Coleman, 1990; Fukuyama, 1995) and improvesthe aggregate productivity of a society (Sollow,2000). In contrast, social conflict poses a threatto business activities, because it reduces the effi-ciency of cross-border economic activities (Ghe-mawat, 2001). In sum, economic, political, andsocial institutions form the institutional environ-ment within which firms carry out their businessactivities and from which they gain a return ontheir investments.

HYPOTHESIS DEVELOPMENT

Institutional development and the level offoreign affiliate performance

Countries differ markedly in their institutionalenvironments and in the extent to which their insti-tutions are developed (Ghemawat, 2001; Kostovaand Zaheer, 1999; Miller and Eden, 2006; Rosen-zweig and Singh, 1991; Westney, 1993; Zaheer,1995). These between-country differences createunique challenges for foreign affiliates, becauseinstitutions alter the costs of engaging in busi-ness activities in one host country compared withanother host country (Henisz, 2004).

The level of institutional development in emerg-ing economies is relatively low, largely becauseinstitutional rules are absent, insufficient, or poorlyenforced (Hitt et al., 2004; Hoskisson et al., 2000;Khanna and Palepu, 1997; North, 1990; Peng andHeath, 1996). A lack of reliable market informa-tion, efficient intermediary institutions, predictablegovernment actions, and an efficient bureaucracycreates what are known as ‘institutional voids’



(Khanna and Palepu, 1997, 2000a). Such institu-tional voids make market transactions costly andtransformation less efficient for foreign affiliates,because institutions lack the cognitive or moralbasis for legitimacy (Henisz and Zelner, 2005).Transaction costs are increased because foreignfirms need to protect their assets from expropri-ation, usually through the use of mobile assets andpolitical risk loans (Bergara et al., 1998; Henisz,2000b), to prevent the unwanted dissemination oftheir proprietary assets (Delios and Beamish, 1999;Meyer, 2001) and to engage in local corrupt trans-actions that penalize efficient firms (Rodriguezet al., 2005; Tanzi, 1998). Transformation costs areraised because underdeveloped institutions mean agreater risk of unenforceable contracts and inse-cure property rights, which lead firms to adoptinferior technology and thus operate less efficientlyand competitively (North, 1990).

Foreign affiliates that operate in countries witha low level of institutional development are likelyto engage in costly market transactions and lessefficient transformation, whereas foreign affiliatesthat operate in countries with a higher level ofinstitutional development can capitalize on theadvantages generated by the presence of better-developed institutions. Institutional developmentresults from the implementation of financial mar-ket and economic policies (Collier and Gunning,1999; Levine and Zervos, 1998; Nelson and Singh,1998; Rajan and Zingales, 1998), the improvementof the provision of public goods (Boix, 2001), theefficiency of intermediation (Khanna and Palepu.,2000a), and the reduction of the extent of cor-ruption (Mauro, 1997). Better-developed institu-tions play a role in facilitating interactions thatreduce uncertainties and that lower transaction,search, and production costs (Akerlof, 1970; Dia-mond, 1984; Khanna and Palepu, 1997; Khannaand Rivkin, 2001; North, 1990), although the out-comes generated by better-developed institutionsare beyond normative evaluation (Henisz and Zel-ner, 2005). Countries with better-developed institu-tions provide a more favorable institutional contextfor foreign affiliates, which in turn has a posi-tive effect on the profitability of foreign operations(Bergara et al., 1998; Levy and Spiller, 1994).

In sum, we expect a positive relationship bet-ween the level of institutional development andthe level of foreign affiliate performance. How-ever, this positive relationship is likely to plateauat a certain high level of development, such that in

institutionally well-developed countries the pres-ence of well-functioning institutions may fail tofurther reduce transaction costs beyond a cer-tain level because of the complexity of exchange(North, 1990) or the existence of transaction haz-ards (Peng, 2003; Williamson, 1985). Well-developed market-supporting institutions may alsofacilitate more new entries into the market (Peng,2003), which will inevitably drive up the costs ofengaging in business activities for foreign affiliatesand thus affect their performance (Miller and Eden,2006). This argument is parallel to the densitydependence argument, which states that institu-tional pressures give way to competitive pressuresas the population matures (Carroll and Hannan,1989; Hannan and Carroll, 1992). We thereforehypothesize the following:

Hypothesis 1: The level of institutional develop-ment has a positive curvilinear relationship withthe level of foreign affiliate performance.

Institutional development and variation inforeign affiliate performance

We argue in the foregoing section that the averageforeign affiliate performance is likely to be lowin institutionally underdeveloped host countries.However, not all foreign affiliates suffer from thesame low level of profitability. We argue that theperformance of foreign affiliates varies greatly inhost countries with a low level of institutionaldevelopment, and that such variation comes fromtwo sources: a lack of legitimate strategic choicesthat have known outcomes and differences in theinstitutional ability of foreign affiliates to handleinstitutional idiosyncrasies.

Variation in the performance of foreign affiliatescan be attributed to a lack of legitimate strate-gic choices that have known outcomes. In hostcountries in which the level of institutional devel-opment is low, institutions may fail to reduceuncertainty in transactions between parties in cap-ital, product, and labor markets (North, 1990). Forexample, host governments may not credibly com-mit not to appropriate property rights or overturninvestment policies (Fischer, 1980, Henisz, 2000a),and intermediaries may not be able to crediblycommunicate information between transaction par-ties or resolve information problems (Khanna andPalepu, 1997, 2000a). As institutions in these hostcountries remain underdeveloped, they may not



be able to determine what constitutes legitimateorganizational activities within their institutionalcontext (Henisz and Zelner, 2005; Scott, 1995;Suchman, 1995). In this situation, foreign affiliatesface greater uncertainty about legitimate ways ofdoing business, and are thus likely to engage in awider range of strategic actions so as to overcomethe institutional voids present in these host coun-tries.1 The outcomes of the strategic actions arelikely to be unknown because foreign affiliates lackprior information about the efficiency and effec-tiveness of their strategies (Chan, Makino, andIsobe, 2006). As some strategic actions are ableto generate rents by overcoming the institutionalvoids whereas others are not, the performance out-comes of different strategic choices are likely tovary greatly.

Variation in the performance of foreign affili-ates can also be attributed to differences in theinstitutional ability ex post to manage institutionalidiosyncrasies. In institutionally underdevelopedcountries, the institutional ability to manage insti-tutional idiosyncrasies is of strategic importancein the generation of rents (Henisz, 2003). Foreignaffiliates that have sufficient institutional ability tomanage the institutional idiosyncrasies of the hostcountry will have a better chance of achieving bet-ter performance than those without this ability. Asforeign affiliates vary in their ability to manageinstitutional idiosyncrasies, we expect great perfor-mance variation among affiliates in institutionallyunderdeveloped countries.

In contrast, better-developed institutions canbestow social acceptance on organizational activ-ities and constrain the strategic choices of firms

1 Prior literature suggests several reasons for variations in orga-nizational actions under uncertainty. For example, drawing onAshby’s (1956) law of requisite variety, Miles, Snow, and Sharf-man (1993) argue that firms in an industry must possess avariety of actions requisite to their environments. Organizationalecologists suggest that ‘specialist’ and ‘generalist’ firms pursuedifferent strategies within an industry and that ‘generalist’ firmstend to outperform ‘specialist’ firms under uncertainty (Hannanand Freeman, 1977). Other researchers argue that organizationshave distinct mechanisms of making sense of uncertainty, suchas information processing capacity (Tushman and Nadler, 1978;Galbraith, 1973), slack resources (Burns and Stalker, 1961),interpretation systems (Daft and Weick, 1984), and dominantlogic (Prahalad and Bettis, 1986), which lead to variations inorganizational actions. Simon (1976) also argues that decisionmakers are inherently bounded rational and have a wide rangeof cognitive biases about the handling of uncertainty. Carroll(1993) compares and contrasts major theoretical perspectives onwhy firms differ.

(Henisz, 2003; Hitt et al., 2004; Ingram and Silver-man, 2002; Oliver, 1997; Peng, 2002, 2003; Pengand Heath, 1996), as the structures, processes, andconsequences of the institutions are beyond nor-mative evaluation as a result of having attainedlegitimacy (Henisz and Zelner, 2005). In this situ-ation, firms tend to follow legitimate organizationalpractices or strategic actions with known outcomesto increase their chances of survival (DiMaggioand Powell, 1983; Peng, 2003; Scott, 1995). Theadoption of similar strategic actions is, therefore,likely to lead to less performance variation amongforeign affiliates. In addition, when the institu-tional environment of the host country is betterestablished, the institutional ability ex post thatis needed to manage institutional idiosyncrasies isof diminishing importance (Child and Tse, 2001;Hoskisson et al., 2000; Peng, 2003; Peng, Lee, andWang, 2005), and thus as foreign affiliates that lackthis ability are not at a disadvantage, we expect lessperformance variation among affiliates in institu-tionally better-developed countries.

In sum, we expect a negative relationship bet-ween the level of institutional development andthe variation in foreign affiliate performance. How-ever, the negative relationship will plateau at acertain high level of institutional development.In host countries in which institutions are verywell developed, variations in firm performancewill be greater because of the differences in com-petitive advantages among firms (Oliver, 1997;Peng, 2003). Hoskisson et al. (2000) suggest thatresource-based strategies, which focus on firm-specific resources and capabilities, become morerelevant than institution-based strategies, whichfocus on legitimacy and institutional ability, ashost country institutions develop. This notion hasgained support in the study of Makino et al. (2004)to find that firm effects (firm-specific resources andcapabilities) tend to play a more salient role thancountry effects (host country attributes and insti-tutions) in explaining variations in foreign affiliateperformance in developed countries. We thereforeexpect greater variation in foreign affiliate perfor-mance in host countries with a high level of institu-tional development, because foreign affiliates varyin the firm-specific resources that they possess andin their capability to compete for market oppor-tunities (Barney, 1986; Chang, 1995; Kogut andZander, 1993). We therefore hypothesize the fol-lowing.



Hypothesis 2: The level of institutional devel-opment has a negative curvilinear relationshipwith the variation in foreign affiliate perfor-mance.

METHODOLOGY

Data

Our data are derived from the Trend Survey ofOverseas Business Activities (hereafter the TrendSurvey),2 which gathers information about thebusiness activities of the foreign affiliates ofJapanese corporations. The Trend Survey has beenconducted annually by the Japanese Ministry ofEconomics, Trade, and Industry (METI) since1971. The survey covers all Japanese corporationsthat have affiliates in overseas markets, excludingthose in the real estate, financial, and insuranceindustries. The foreign affiliates of Japanese cor-porations are of three types: (1) foreign affiliates inwhich a Japanese corporation has invested capitalof 10 percent or more (a subsidiary), (2) foreignaffiliates in which a subsidiary that is more than50 percent funded by a Japanese corporation hasinvested capital of more than 50 percent in total (asub-subsidiary), and (3) foreign affiliates in whicha Japanese corporation and a sub-subsidiary thatis more than 50 percent funded by a Japanese cor-poration have invested capital of more than 50percent in total. Survey forms, which included onefor the parent firm and one for each of its foreignaffiliates, were sent to Japanese corporations.

We used six annual reports of the Trend Surveyfor the period 1996–2001 to compile our paneldataset. We selected 38 countries in which 12 ormore foreign affiliates were established during theobservation period.3 Our panel dataset containsa sample of more than 30,000 foreign affiliate-year cases that include 6,985 foreign affiliates

2 This database has been used in the studies of Kiyota et al.(2005) and Makino et al. (2004). Detailed information on theTrend Survey of Overseas Business Activities can be found on theMETI Web site at http://www.meti.go.jp/english/statistics/tyo/kaigaizi/index.html.3 Some researchers argue that the variation in foreign affiliateperformance is influenced by sample size (the number of casesin each host country). To examine this possible sampling bias,we examine the correlation between the sample size and theaverage standard deviation of the return on sales (ROS) in eachhost country. The result suggests a weak correlation betweenthese variables (r = 0.127), and we therefore conclude that thesampling bias in our analysis is not critical.

established by 1,421 Japanese corporations in 38countries across 169 industries (three- to four-digit SIC codes). The average response rate ofthe survey during the observation period was 60.9percent.

Variables

Dependent variables

Our dependent variables are the level of and vari-ation in foreign affiliate performance. The levelof foreign affiliate performance (return on invest-ment) is measured by the return on sales (ROS) ofthe foreign affiliates of MNCs. We use ROS, ratherthan return on assets (ROA), as the measure of thereturn on investment for two reasons. First, ROSis regarded as a superior measure in the globalenvironment (Lincoln, Gerlach, and Ahmadjian,1996), because foreign affiliates—and especiallystrategic alliances—focus on ongoing businesses,and therefore sales (the numerator of ROS) bet-ter reflect their performance across changes inthe business climate than fixed assets (Christmannet al., 1999). Second, asset turnover may vary sig-nificantly among host countries due to differencesin their market value, which means that ROA maynot correctly reflect the economic performance offoreign affiliates.

The variation in foreign affiliate performance(risk of investment) is measured by the extentto which the ROS of foreign affiliates deviatesfrom the host country mean. Previous studiesmeasure risk in a variety of ways, including thevariance in the income stream (Bowman, 1980;Ruefli, 1990), below-target performance (Millerand Reuer, 1996), and the probability of bankru-ptcy (March and Shapira, 1992). Our measure ofrisk is similar to the traditional variance-basedmeasure of risk (or standard deviation), but dif-fers in two ways. First, our measure captures thevariation in foreign affiliate performance, whereasthe conventional variance-based measure capturesthe variation in business unit performance. Sec-ond, our measure controls for the systematic effectson return streams that vary across host countries,which the conventional variance-based measureomits. Our measure of risk thus captures the varia-tion in performance among foreign affiliates withina host country in each year, rather than the varia-tion in performance within a business unit acrossyears.



Risk can be measured by the variance in down-side return streams (i.e., unexpected negative out-comes) or by the variance in both downside andupside return streams. In this study, we take thesecond approach for two reasons. First, firms havedifferent reference points that they use to setthe expected level of performance to which theyaspire, and these reference points vary significantlyacross firms and across contexts (Sitkin and Pablo,1992). This implies that the range of ‘downsiderisk’ is blurred among firms and contexts, and isthus difficult to specify. Second, firms may makea decision to enter a particular host country basednot only on information about the previous neg-ative return streams of the incumbents, but alsoon information about their previous positive returnstreams. For example, research has suggested thatrisk-averse firms tend to place a greater value onprevious positive return streams than on previousnegative return streams (Kahneman and Tversky,1979). Therefore, the measure of variance-basedrisk must incorporate both the downside and upsidestreams of returns.

The operational definitions of the risk of invest-ment and return on investment are expressed in thefollowing equations.

Returni,t = ROSi,t

Riski,t =√

(ROSi,t − ROSc,t )2,

where Returni,t is the ROS of the i th foreignaffiliate in the t th year and Riski,t is the absolutevalue of the deviation between the ROS of thei th foreign affiliate in the t th year and the meancountry ROS in the t th year (ROSc,t ). We focuson both the risk of investment and the returnon investment because increasing importance isaccorded the risk-return relations that underlie thestrategic behavior of firms, as the strategic choicesof investment of firms are often endogenous totheir desired outcomes (Bromiley, Miller, and Rau,2001; Ruefli, Collins, and Lacugna, 1999).

Independent variables

To measure the level of institutional developmentof a host country, we use 12 national institutionalcharacteristics as proxies for economic, politi-cal, and social institutions (see Appendix I). Weobtained the data from the World CompetitivenessYearbook, International Monetary Fund, Freedom

House, and International Country Risk Guide (PRSGroup) for the period 1996–2001. These databaseshave been widely used in other empirical studies(Barro, 1991, 1996; Guillen, 2000; Hall and Jones,1999; Henisz, 2000a; Knack and Keefer, 1997; LaPorta et al., 1997; Wan and Hoskisson, 2003; Yiuand Makino, 2002). We conducted a principal com-ponents analysis with a varimax rotation for all12 items for each year.4 The items loaded signif-icantly on one factor (institutional development)with an eigenvalue of 7.51–8.60, and explained68.0–71.4 percent of the variance. We also con-ducted confirmatory factor analyses to evaluatethe one-factor model based upon the result ofthe exploratory factor analysis and a three-factormodel that reflects the three constructs of institu-tional development (economic, political, and socialinstitutions). The differences in fit between themodels were estimated using chi-square differencetests. The results of the analyses for the six-yearperiod show that the chi-square values do not dif-fer significantly between the one- and three-factormodels (the �χ 2s fall within the range of 0.44to 4.86, d.f. = 3, p > 0.1), and that the three-factor model does not provide a significantly betterfit than the one-factor model. We calculated theinstitutional development scores for each countryand compiled an ‘Institutional Development Index’(IDI), as shown in Appendix II. We included bothlinear and quadric terms in the models to testthe hypothesized curvilinear effects of institutionaldevelopment.

Validity check

To examine the validity of the IDI, we per-formed correlation analyses between the IDI andother institutional measures to examine whetherthe IDI gives results that are consistent withother institutional measures from the World Bank,Heritage Foundation, OECD Development Cen-tre, Economist Intelligence Unit, World EconomicForum, World Values Survey, United NationsDevelopment Programme, Internet Center for Cor-ruption Research, Japan Center for Economic Re-search, and Business Software Alliance of thedevelopment of economic, political, and socialinstitutions. Although we are not able to show the

4 The score of the item ‘Harassment and violence’ was notavailable for the year 1996. The IDI for the year 1996 wastherefore calculated using 11 items.



correlations among the IDI and the other institu-tional measures for every year due to the unavail-ability of all of the data for the measures forall years, the results of the correlation analysesshow the IDI to be strongly correlated with theother measures, with all of the correlation coeffi-cients being significant at the p < 0.001 level (seeAppendix III). For example, the IDI has a highcorrelation with the Heritage Foundation Indexof Economic Freedom in the observation period(1996–2001) (between 0.783 and 0.855), and the2000 score of our index also has a high correla-tion with the 2000 institutional measures of theWorld Bank (between 0.824 and 0.975). Thesestrong positive correlations indicate that the IDIand other institutional measures developed by vari-ous research institutions track a similar underlyingphenomenon of institutional development. How-ever, we believe that the IDI improves upon thestate-of-the-art measures in the field, because itcaptures the development of all three institutionsin host countries (economic, political, and social).

Control variables

We control for the country-, industry-, parent firm-,and foreign affiliate-level variables that may influ-ence the level of and variation in foreign affili-ate performance. Conventional studies that drawon the resource-based view of the firm suggestthat firm-specific idiosyncrasies in the accumu-lation and leverage of unique resources are themajor sources of competitive advantage for firms(Barney, 1991; Wernerfelt, 1984). An MNC canbe viewed as a collection of underutilized, tacitresources that are embedded in a global net-work (Chang, 1995; Kogut and Zander, 1993),and in this sense the parent firm-level competitiveadvantages include firm-specific capabilities andknow-how, such as patented design and processes(Caves, 1996), and corporate-wide capabilities thatfacilitate collective learning among business units(Bartlett and Ghoshal, 1989; Prahalad and Hamel,1990). We control for two types of parent firmresources: parent firm size and international expe-rience. Parent firm size, which is measured by firmsales, represents the size of the available pool ofresources or capabilities that can be exploited in anew market (Hymer, 1960/1976; Penrose, 1959).Previous studies suggested that MNCs with uniqueresources are able to generate high returns fromtheir foreign operations because of economies of

scale and scope (Kotabe, Srinivasan, and Aulakh,2002; Morck and Yeung, 1991). The interna-tional experience of the parent firm represents thecapability of MNCs to manage foreign affiliates.Previous research suggests that international expe-rience tends to mitigate the risks associated withuncertainty in foreign operations, and hence hasa positive effect on foreign affiliate performance(Delios and Beamish, 2001; Makino and Delios,1996). This variable is measured by a dummyvariable that is coded ‘1’ if the parent firm estab-lished two or more foreign affiliates in the samehost country and ‘0’ otherwise. We obtained thesevariables from the annual volumes of the TrendSurvey.

The industrial organization economics perspec-tive suggests that the structural characteristics ofindustries constrain the behavior of firms and thusare key determinants of long-term performance(Porter, 1980). Previous studies show that the vari-ation in industry attributes explains the variation inbusiness unit performance and foreign affiliate per-formance (Christmann et al., 1999; Makino et al.,2004; McGahan and Porter, 1997; Rumelt, 1991),and that the effects of industry tend to be greaterwhen an industry is defined at a ‘local’ level(i.e., an industry that is separately defined withineach host country) than when it is defined at a‘global’ level (i.e., an industry that spans differenthost countries) (Chan et al., 2006). We thereforeinclude industry-country dummies, which describeindustries within each host country, to controlfor the possible influence of industry and hostcountry type on foreign affiliate performance.The industry classification of foreign affiliatesis based on the list of industries reported inthe Trend Survey, which follows the three- orfour-digit SIC code (Makino et al., 2004). Theindustry-country dummies represent 1,442 com-binations of industries and host countries in oursample. The other industry-level control variablethat we include is local density, which is mea-sured as the number of other foreign affiliatesin the same industry in a host country. Recentresearch on density dependence models of orga-nizations suggests that firms are under strongercompetitive influences at the local or regionallevel, as they compete more intensely in the localenvironment (Baum and Oliver, 1996; Baum andSingh, 1994; Bigelow et al., 1997; Chan et al.,2006; Hannan et al., 1995; Lomi, 1995). Therecent study of Miller and Eden (2006) provides



evidence that local density, which represents com-petitive pressures, has a negative influence on for-eign affiliate performance, because rents to thehome-based advantages of foreign affiliates aresqueezed in a highly competitive local market.We therefore control for the possible downwardeffect of local density on foreign affiliate perfor-mance. The data for this variable were obtainedfrom the 1996–2001 annual volumes of ToyoKeizai’s Directory of Japanese Overseas Affili-ates.

We also control for other possible country-levelfactors that influence foreign affiliate performance,namely, labor cost and geographic distance. Tradi-tional trade theory suggests that countries differ inthe relative cost and availability of the factors ofproduction, such as labor and natural resources,and that these differences in factor costs makeinvestment in some countries more advantageousthan in others (Dunning, 1988). We include thevariable of labor cost, as measured by the totalhourly compensation for manufacturing workers,to control for its possible downward effect on for-eign affiliate performance. We obtained the datafrom the Bureau of Labor Statistics (U.S. Depart-ment of Labor).5 Geographic distance is includedto control for its possible downward effect onforeign affiliate performance, as previous stud-ies suggest that geographic distance between thehome country and the host country affects thecosts of transportation and communications (Ghe-mawat, 2001; Hymer, 1960/1976; Zaheer, 1995).We obtained the data on geographic distance fromthe study of Boisso and Ferrantino (1997), andmeasure the variable by the radians of the unitcircle between the centroids of the home and hostcountries. Other unobserved host country effectsare, again, controlled by industry-country dum-mies.

The first foreign affiliate-level control variablethat we include is the operational purpose of for-eign affiliates in the host country. We obtainedthe data from the Trend Survey, which reports theoperational purpose of a firm as selected from alist of 12 items. We conducted a principal com-ponents analysis with a varimax rotation for all12 of these items, which we then categorized

5 More information on the International Comparisons of HourlyCompensation Costs for Production Workers in Manufacturingcan be found on the Bureau of Labor Statistics Web site atwww.bls.gov/home.htm.

into seven constructs: resource seeking (gainingaccess to natural resources and low-cost labor inhost countries), market seeking (exploring marketopportunities for sales in local markets), strate-gic asset seeking (gaining access to knowledgeand technology in the host country), followingcustomers (following customers to enter overseasmarkets for the supply of parts and components totheir overseas production sites), portfolio manage-ment (transferring dividends or profits to parentfirms), risk hedging (hedging for exchange raterisks), and exporting (exporting products to Japanor other countries). All of the constructs are mea-sured by dummy variables that take the value of‘1’ if the foreign affiliate was established for theoperational purpose in question and ‘0’ otherwise.Another affiliate-level control variable is affiliateage, which is measured by the number of yearsbetween the establishment of the foreign affiliateand the end of the observation period. This vari-able is included to control for the possible effectof the liability of newness (Stinchcombe, 1965) onforeign affiliate performance. Finally, we includeparent firm and year dummies to control for theirunobserved influence on foreign affiliate perfor-mance. A correlation matrix of all of the variablesis provided in Table 1.

Analysis

Our data are compiled in a panel dataset. As thedata contain repeated observations of the same sub-sidiary across years, we need to control for poten-tial biases caused by a lack of independence inthe observations, which may create heteroscedas-ticity and serial correlation problems. We chosethe generalized estimating equations (GEE) modelto correct for these problems (Liang and Zeger,1986), which assumes a first-order autoregressivecorrelation structure within each foreign affiliate.This method can account for biases caused bythe correlations between repeated observations.6

6 Several researchers have used a Hausman test to examinewhether random effects (in our case, unobserved foreign-affiliatespecific effects) are correlated with the observed predictorsin regression models. If they are correlated, then a randomeffect model will produce biased estimators, and thus a fixedeffects model should be chosen instead. As with a randomeffects model, the GEE cannot control for any stable unobservedcharacteristics of the foreign affiliates, and thus may producebiases. Unfortunately, the GEE in the GENMOD Procedurein SAS cannot perform a Hausman test, so as an alternativewe used the group-mean centering method for fixed effects



A first-order autocorrelation was specified withinunits and validated by the pooled Durbin-Watsonstatistic for the corrected sample. We dealt withthe heteroscedasticity issue by applying the Huber-White sandwich estimator of variance instead ofthe traditional variance calculation (White, 1982).We report the robust standard errors for the regres-sion parameters and the Wald chi-square statistics,which test the null hypothesis that all of the regres-sion coefficients are equal to zero.

FINDINGS

Figure 1 presents a scatter plot of the level of andvariation in foreign affiliate performance acrosscountries (see Appendix IV for the list of coun-try means). The overall country average level ofROS is 1.61 percent and the overall country aver-age variation in ROS is 6.55. In the advanced

estimates (Allison, 2005). The results of the analysis showedtwo predictor variables to be significantly correlated with theunobserved foreign affiliate-specific effects. We removed thesevariables and ran the test again, and the results showed nosignificant correlations between the unobserved foreign affiliate-specific effects and the predictor variables, both separately andfor all of the variables together (chi-square = 10.02, d.f. = 6,p = 0.124 for the return model and chi-square = 2.99, d.f. = 6,p = 0.810 for the risk model, for all variables). We can thereforeconclude that our GEE models produce no critical biases.

economies, the level of ROS is close to the over-all average and the variation in ROS is lower thanthe overall average. Most countries with advancedeconomies (e.g., the United States, France, andGermany) fall into the ‘low risk (low variationin ROS)–low return (low level of ROS)’ cate-gory. The foreign affiliates in most of the EuropeanUnion (EU) countries have a lower average returnthan those in non-EU countries, such as Canadaand Australia.

The level of ROS varies noticeably among theemerging economies.7 Foreign affiliates in Thai-land and China appear to have lower returnsthan those in Indonesia, India, Brazil, and thePhilippines, whereas foreign affiliates in Mexico,Malaysia, and Pakistan are found to have higherreturns. The variation in ROS in almost all ofthe emerging economies is greater than the overallaverage. Countries that attract many foreign affili-ates (e.g., Indonesia, Thailand, and China) fall intothe ‘high risk (high variation in ROS)–low return(low level of ROS)’ category.

7 The level of ROS in Liberia is exceptionally higher than theoverall average (see Appendix IV). According to informationprovided by Toyo Keizai’s Directory of Japanese OverseasAffiliates, there are 21 Japanese foreign affiliates in Liberia, allof which operate in the shipping industry and were established toown or lease ships, and half of which do not have any employees.We therefore consider this to be an exceptional case.

Brazil

Philippines

France

Korea

Germany

MalaysiaHong Kong

Thailand

USA

NetherlandsCanada

Australia

Indonesia

UK

TaiwanSingapore

Italy

Pakistan

Mexico

Spain

Belgium

0

2

4

6

8

10

12

14

16

18

0

Return (level of ROS, %)

Ris

k (v

aria

tion

in R

OS)

Average risk (6.55)

Average return (1.61%)Emerging economiesAsian NIEs

Advanced economies

1 2 3 4 5

India

China

Notes: 1. The figure depicts host countries with more than 50 foreign affiliates.2. The size of the circle represents the number of foreign affiliates.

Figure 1. Scatter plot of the distribution of foreign affiliate performance by country



Tabl

e1.

Des

crip

tive

stat

istic

san

dco

rrel

atio

ns

Mea

ns.

d.1

23

45

67

89

1011

1213

1415

1L

evel

offo

reig

naf

filia

tepe

rfor

man

ce1.

6113

.91

2V

aria

tion

info

reig

naf

filia

tepe

rfor

man

ce6.

5512

.24

−0.3

1∗∗

3In

stitu

tiona

lde

velo

pmen

t−0

.03

0.96

−0.0

1−0

.15∗∗

4L

abor

cost

11.0

37.

88−0

.02∗∗

−0.1

2∗∗0.

74∗∗

5G

eogr

aphi

cdi

stan

ce3.

740.

27−0

.03∗∗

−0.0

6∗∗0.

49∗∗

0.70

∗∗

6L

ocal

dens

ity1.

060.

71−0

.01∗∗

−0.1

1∗∗0.

26∗∗

0.22

∗∗0.

11∗∗

7A

ffilia

teag

e13

.61

9.52

0.05

∗∗−0

.09∗∗

0.12

∗∗0.

15∗∗

0.15

∗∗0.

09∗∗

8Pa

rent

size

5.40

0.95

−0.0

2∗∗−0

.04∗∗

0.01

0.05

∗∗0.

13∗∗

0.01

0.04

∗∗

9In

tern

atio

nal

expe

rien

ceof

pare

ntfir

m0.

510.

500.

00−0

.01

0.00

0.04

∗∗0.

02∗

0.08

∗∗−0

.02∗

0.45

∗∗

10R

esou

rce

seek

ing

0.35

0.48

0.00

0.04

∗∗−0

.26∗∗

−0.2

6∗∗−0

.23∗∗

−0.1

7∗∗−0

.07∗∗

−0.1

6∗∗−0

.01

11M

arke

tse

ekin

g0.

580.

49−0

.02∗∗

−0.0

3∗∗0.

03∗∗

0.06

∗∗0.

03∗∗

0.06

∗∗0.

02∗∗

−0.0

7∗∗−0

.07∗∗

0.12

∗∗

12St

rate

gic

asse

tse

ekin

g0.

030.

180.

000.

02∗∗

0.07

∗∗0.

10∗∗

0.08

∗∗−0

.03∗∗

−0.0

6∗∗−0

.02∗

0.01

−0.0

10.

06∗∗

13Fo

llow

ing

cust

omer

s0.

150.

36−0

.02∗∗

0.01

∗∗−0

.06∗∗

−0.0

7∗∗−0

.05∗∗

0.01

−0.1

0∗∗−0

.13∗∗

−0.0

8∗∗0.

16∗∗

0.15

∗∗−0

.04∗∗

14Po

rtfo

liom

anag

emen

t0.

070.

26−0

.01

−0.0

3∗∗0.

08∗∗

0.08

∗∗0.

06∗∗

−0.0

3∗∗0.

02∗

−0.0

2∗∗−0

.01

0.04

∗∗0.

11∗∗

0.00

−0.0

115

Ris

khe

dgin

g0.

030.

180.

00−0

.04∗∗

0.07

∗∗0.

09∗∗

0.06

∗∗0.

000.

04∗∗

0.02

∗∗0.

01∗

−0.0

10.

10∗∗

0.01

∗−0

.03∗∗

0.65

∗∗

16E

xpor

ting

0.34

0.47

−0.0

2∗∗−0

.03∗∗

0.03

∗∗0.

03∗∗

0.01

0.03

∗∗−0

.01

−0.0

7−0

.05∗

0.19

∗∗0.

39∗∗

0.01

−0.0

2∗∗−0

.01

−0.0

4∗∗

∗ p<

0.01

;∗∗

p<

0.00

1

Among the newly industrialized economies inAsia (Asian NIEs), the level of ROS tends to behigher than the overall average and varies over awider range. Foreign affiliates in Taiwan and SouthKorea appear to have very high returns, whereasthose in Singapore and Hong Kong have averagereturns. The variation in ROS appears to be lowerthan the overall average in all of the Asian NIEs.In sum, Taiwan and South Korea fall into the‘low risk (low variation in ROS)–high return (highlevel of ROS)’ category, whereas Singapore andHong Kong fall into the ‘low risk (low variationin ROS)–average return (average level of ROS)’category.

Table 2 shows the results of the analyses ofthe relationship between the level of institutionaldevelopment and the level of foreign affiliate per-formance. Model 3 shows that the linear term ofinstitutional development has a negative and sig-nificant impact on the level of foreign affiliate per-formance, and that the quadric term of institutionaldevelopment has a nonsignificant positive impact.This finding is inconsistent with our prediction thatthe level of institutional development has a positivecurvilinear relationship with the level of foreignaffiliate performance, and therefore Hypothesis 1is not supported.

Our analyses of the relationship between thelevel of institutional development and the vari-ation in foreign affiliate performance are shownin Table 3. Model 3 shows that the linear termof institutional development has a negative andsignificant impact on the variation in foreignaffiliate performance, whereas the quadric termof institutional development has a positive andsignificant impact. The inflection point ofinstitutional development (0.214) is within therange of observation (−2.251 to 1.458), but iscloser to the right edge of the range. Takentogether, these results offer strong support for ourprediction that the level of institutional devel-opment has a negative curvilinear relationshipwith the variation in foreign affiliate performance,and thus Hypothesis 2 is supported. Figure 2presents a graphic illustration of the effects ofthe level of institutional development on thelevel of and variation in foreign affiliate perfor-mance.

In terms of the impact of the control variableson the level of foreign affiliate performance, theresults suggest that the level of foreign affiliate per-formance is likely to be high when the labor costs



are low, when the geographic distance between thehost country and the home country is small, andwhen the foreign affiliates are older in age andwere established to hedge for exchange rate risks(rather than to explore new market opportunities,follow the international expansion strategy of theircustomers, transfer dividends or profits to the par-ent firm, or export products to Japan and othercountries) (see Models 1 to 3 in Table 2). Theeffects of the control variables on the variation inforeign affiliate performance are shown in Table 3.

The results suggest that the variation in foreignaffiliate performance is likely to be large when thegeographic distance between the host country andthe home country is large and the labor costs low,and when the foreign affiliates are younger in ageand were established to gain access to knowledgeand technology in the host country or to trans-fer dividends or profits to their parent firm (ratherthan to explore new market opportunities, hedgefor exchange rate risks, or export products to Japanand other countries).

Table 2. Regression results for the level of foreign affiliate performancea

Levelb Model 1 Model 2 Model 3

Institutional development C −0.5568∗∗∗ −0.4947∗∗∗

(0.1469) (0.1283)Institutional development2 C 0.1808

(0.1458)Labor cost C −0.0482∗∗ −0.0499∗∗ −0.0495∗∗

(0.0161) (0.0165) (0.0164)Geographic distance C −1.1208∗ −1.1220∗ −0.8612+

(0.4762) (0.4774) (0.4841)Local density I −0.2243 −0.2289 −0.1542

(0.2054) (0.2089) (0.2118)Parent size (log sales) P 0.2658 0.2655 0.2593

(0.7174) (0.7174) (0.7167)International experience of parent firm P −0.0301 −0.0313 −0.0177

(0.2205) (0.2205) (0.2206)Affiliate age A 0.0713∗∗∗ 0.0711∗∗∗ 0.0706∗∗∗

(0.0094) (0.0095) (0.0095)Resource seeking A −0.3735 −0.3716 −0.3615

(0.2571) (0.2575) (0.2573)Market seeking A −0.5742+ −0.5739+ −0.5668+

(0.2951) (0.2950) (0.2950)Strategic asset seeking A −0.4008 −0.4024 −0.4077

(0.6287) (0.6286) (0.6273)Following customer A −0.8861∗ −0.8885∗ −0.9018∗∗

(0.3481) (0.3485) (0.3484)Portfolio management A −0.9401+ −0.9430+ −0.9155+

(0.5056) (0.5048) (0.5047)Risk hedging A 1.5904∗∗ 1.5906∗∗ 1.5418∗

(0.6061) (0.6060) (0.6055)Exporting A −0.3900+ −0.3911+ −0.4070+

(0.2342) (0.2337) (0.2334)Intercept 17.6582∗∗∗ 16.3193∗∗ 16.461∗∗

(5.2641) (5.2899) (5.2885)Parent firm dummy P Included Included IncludedIndustry-country dummy C, I Included Included IncludedYear dummy Included Included Included

Log likelihood −102492.5 −102474.5 −102473.6Log likelihood test 17.9∗∗∗ 18.9∗∗∗

Observations 32,764 32,764 32,764

+ p < 0.1; ∗ p < 0.05; ∗∗ p < 0.01; ∗∗∗ p < 0.001a. The estimates of the parameters are based on Wald chi-squares. The robust standard errors are given in parenthesesb. C = Country level; I = Industry level; A = Affiliate level; P = Parent firm level



Table 3. Regression results for the variation in foreign affiliate performancea

Levelb Model 1 Model 2 Model 3

Institutional development C −0.0910∗∗∗ −0.0469∗∗∗

(0.0233) (0.0107)Institutional development2 C 0.1295∗∗∗

(0.0326)Labor cost C −0.0450∗∗∗ −0.0241∗∗∗ −0.0280∗∗∗

(0.0037) (0.0058) (0.0054)Geographic distance C 0.3946∗∗∗ 0.3634∗∗∗ 0.3210∗∗∗

(0.0803) (0.0808) (0.0861)Local density I 0.0303 0.0720 0.0236

(0.0640) (0.0630) (0.0586)Parent size (log sales) P −0.0643 −0.0485 −0.0424

(0.0170) (0.1164) (0.1549)International experience of parent firm P −0.0467 −0.0242 −0.0472

(0.0617) (0.0613) (0.0586)Affiliate age A −0.0167∗∗∗ −0.0140∗∗∗ −0.0130∗∗∗

(0.0029) (0.0029) (0.0029)Resource seeking A 0.0425 0.0310 0.0524

(0.0521) (0.0511) (0.0516)Market seeking A −0.1356∗ −0.1090∗ −0.0909+

(0.0533) (0.0512) (0.0512)Strategic asset seeking A 0.8973∗∗∗ 0.8424∗∗∗ 0.8365∗∗∗

(0.1902) (0.1878) (0.1809)Following customers A 0.0202 0.0247 0.0260

(0.0591) (0.0600) (0.0617)Portfolio management A 0.2255∗∗ 0.2624∗∗ 0.2312∗∗

(0.0830) (0.0847) (0.0847)Risk hedging A −0.4464∗∗ −0.4241∗∗ −0.4128∗∗

(0.1553) (0.1479) (0.1439)Exporting A −0.1556∗∗ −0.1477∗ −0.1642∗∗

(0.0586) (0.0583) (0.0573)Intercept 0.0306 −0.2651 −0.2045

(0.9070) (0.8739) (0.8799)Parent firm dummy P Included Included IncludedIndustry-country dummy C, I Included Included IncludedYear dummy Included Included Included

Log likelihood −122763.3 −122707.7 −122627.9Log likelihood test 55.6∗∗∗ 135.4∗∗∗

Observations 32,764 32,764 32,764

+ p < 0.1; ∗ p < 0.05; ∗∗ p < 0.01; ∗∗∗ p < 0.001.a. The estimates of the parameters are based on Wald chi-squares. The robust standard errors are given in parenthesesb. C = Country level; I = Industry level; A = Affiliate level; P = Parent firm level

DISCUSSION

A key motivation of this study is to examine theperformance of foreign affiliates of MNCs from theneo-institutional perspective. Conventional studiesthat draw on the industrial organization economicsperspective and the resource-based view of thefirm generally suggest that industry structure anda firm’s resources and capabilities are the pri-mary determinants of firm performance. Our studyshows the institution-based view of firm perfor-mance to be a fitting adjunct to the conventional

industry- and resource-based view of firm perfor-mance. Specifically, we suggest that the perfor-mance of foreign affiliates is also influenced by theinstitutional context of the host country in whichthe affiliate is embedded, because host countryinstitutions affect the costs of engaging in businessactivities and the strategic choice of action.

Our evidence clearly shows that the performanceof foreign affiliates varies greatly in institution-ally underdeveloped countries. We argue that suchvariation exists for two reasons. First, a lack ofinformation on legitimate ways of doing business



-1.0

0.0

1.0

2.0

3.0

4.0

5.0

-2.5 -2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5

Institutional development

Lev

el o

f an

d va

riat

ion

in R

OS

Level of foreign affiliate performance

Variation in foreign affiliate performance

Figure 2. Institutional development and the level of and variation in foreign affiliate performance

prompts foreign affiliates to engage in a widerrange of strategic actions with uncertain perfor-mance outcomes. Second, foreign affiliates differin their institutional ability to manage institutionalidiosyncrasies, which is of strategic importance inthe generation of rents in institutionally underde-veloped countries (Henisz, 2003). In contrast, ininstitutionally better-developed countries, the per-formance variations among foreign affiliates willbe less because better-developed institutions con-strain the range of legitimate strategic actions, andthe outcomes of these actions are more certain.Another reason is that the institutional ability tomanage institutional idiosyncrasies is of dimin-ishing importance. In host countries with verywell-developed institutions, the variation in foreignaffiliate performance will be greater, because for-eign affiliates vary in their firm-specific resourcesand capabilities, and these are more relevant deter-minants of performance than institutional abilityin such countries (Hoskisson et al., 2000). In sum,our findings show support for the argument thatthere is a negative curvilinear relationship betweenthe level of institutional development and the vari-ation in foreign affiliate performance.

However, the evidence does not support ourargument that the performance of foreign affili-ates will be lower in institutionally underdevel-oped host countries and higher in institutionallybetter-developed host countries. Indeed, our find-ings show a negative relationship between thelevel of institutional development and the level of

foreign affiliate performance. This evidence con-tradicts the notion that ‘institutional voids’ makemarket transactions costly and transformation lessefficient for foreign affiliates (Khanna and Palepu,1997, 2000a), and that better-developed institu-tions reduce uncertainties and lower transaction,search, and production costs (Akerlof, 1970; Dia-mond, 1984; Khanna and Palepu, 1997; Khannaand Rivkin, 2001; North, 1990). A possible expla-nation for this unexpected finding is that the neg-ative effects of institutional development appearmore strongly than the positive effects, probablybecause of the relatively short period of obser-vation (1996–2001). To adequately examine thehypothesized positive curvilinear effects of insti-tutional development, a longer observation periodmay be required. Another possible explanation isthat foreign affiliates may be more greatly affectedby the low costs of the factors of production (e.g.,labor, land, and natural resources) than the highcosts of transaction and transformation in institu-tionally underdeveloped countries. In support ofthis view, our findings indicate that labor costand geographic distance have a significant nega-tive impact on the level of foreign affiliate per-formance. However, the results of our analysesmay also be explained by a survivor bias. Asour sample includes only surviving foreign affil-iates, it could be argued that unsuccessful for-eign affiliates have a higher rate of terminationin institutionally underdeveloped countries than ininstitutionally better-developed countries. Another



possible explanation is that the market opportu-nities in institutionally underdeveloped countriesmay compensate for the high costs of transac-tion and transformation, because early movers mayhave greater advantages in institutionally underde-veloped countries than in more advanced coun-tries (Isobe, Makino, and Montgomery, 2000).Although we control for the possible influencesof the cost of the factors of production and theintensity of competition in the local market, futureresearch could contribute to this line of inquiryby examining the rationale behind the negativeinfluence of institutional development on foreignaffiliate performance.

We also provide another interesting result onthe relationship between the level of and vari-ation in foreign affiliate performance. Our find-ings show that some emerging economies, suchas China, Thailand, and Indonesia, fall into the‘high risk-low return’ category. Analyzing this evi-dence is of particular interest, because the con-ventional financial portfolio theory cannot explainwhy some countries with emerging economies fallinto this category. Previous studies show that anegative risk-return association has been widelyobserved among U.S.-based diversified firms (Bet-tis, 1981; Bowman, 1980). Future research couldextend this line of inquiry in the international con-text to explain why MNCs get stuck with ‘highrisk-low return’ investments, and how they man-age their diversified international portfolios.

Implications for theory building

Our study has several implications for the devel-opment of an institution-based view of the firm.First, it highlights that researchers could developmore robust conceptual arguments that explain themechanisms by which host country institutionsinfluence firm performance. The results suggestthat host countries at different levels of institu-tional development have a different influence onthe performance of foreign affiliates by drawingon three major theoretical arguments: the presenceof institutional voids, the legitimacy of strategicchoices of action, and the importance of the institu-tional ability to handle institutional idiosyncrasies.The first explains the between-country differencesin foreign affiliate performance, whereas the lattertwo explain the within-country differences in for-eign affiliate performance. To extend these ideas,

future research could carry out a detailed exam-ination of the processes through which institu-tional development influences the between-countrydifferences in foreign affiliate performance, andthe relative influences of institutional ability andstrategic choices of action on the within-countrydifferences in foreign affiliate performance.

Second, researchers could identify the relevantboundaries of host country institutions. We arguethat economic, political, and social institutionstogether determine the level of and variation inforeign affiliate performance, because these insti-tutions are intertwined with one another and canbe integrated to represent the level of institutionaldevelopment of a host country. However, the mag-nitude of influence of each of the three institutionson foreign affiliate performance may differ amongforeign affiliates, because, for example, some for-eign affiliates may be more vulnerable to foreignexchange controls than to corruption and agencyproblems in the host country. A natural extensionof this study would therefore be to examine themechanisms that underlie the varying influences ofthe three institutions, and to explore whether eachinstitution has different influences on the return oninvestment and risk of investment in different hostcountries.

Third, researchers could identify the relevantlevels of analysis for examining the influence ofinstitutions on firm performance. By focusing onthe host country as a primary level of analysis, ourstudy examines the influence of institutional devel-opment on foreign affiliate performance. However,our results indicate that the effects of institutionsmay spread beyond national boundaries, as foreignaffiliates in countries that are regionally integrated,such as the EU, tend to exhibit a very similarpattern of performance. This implies that the per-formance of foreign affiliates is influenced not onlyby host country-specific institutions, but also byregion-specific institutions. Future studies shouldpay attention to the level of analysis and exam-ine both the levels of institutions that have thegreatest influence on foreign affiliate performanceand the conditions under which foreign affiliateperformance is more likely to be influenced byregion-specific institutions than by country-specificinstitutions, and vice versa.

Fourth, researchers could seek to explain howthe institution-based argument adds value to con-ventional explanations of firm performance advo-cated by the industrial organization economies



perspective and the resource-based view of thefirm. Our study argues that host country insti-tutions have a stronger influence on the varia-tion in foreign affiliate performance in institution-ally underdeveloped countries than in institution-ally well-developed countries, because institution-based strategies give way to resource-based strate-gies as host country institutions develop(Hoskisson et al., 2000). To advance our under-standing of the institution-based view of the firm,it would be interesting to explore how industry-and firm-specific factors jointly influence firm per-formance together with host country institutionsand other country-specific factors (e.g., factors ofproduction and technology). Future research couldalso develop theoretical arguments about the wayin which host country institutions moderate theinfluences of firm-, industry-, and country-specificattributes on foreign affiliate performance, andcould provide practical implications for managersof MNCs and policymakers.

Implications for business practice andpolicymaking

Our findings have several implications for busi-ness practice and policymaking. Establishing for-eign affiliates in institutionally underdevelopedhost countries does not necessarily generate alower return on investment, and establishing affil-iates in institutionally well-developed host coun-tries does not necessarily guarantee higher prof-its. Thus, before choosing the location of theirforeign direct investment, managers of MNCsshould address the issue not only of whethertheir foreign affiliates would be better off in aparticular host country, but also of how theycan improve their performance given the insti-tutional constraints of the chosen host country.Our study suggests that some foreign affiliatesoutperform other foreign affiliates because theytake strategic actions to overcome institutionalvoids in the local market. However, it is impor-tant to recognize that the ability to handle institu-tional idiosyncrasies in the local market (Henisz,2003; Oliver, 1997) is different from the abil-ity to build competitive advantages over rivalsin a particular market segment. To successfullymanage institutional idiosyncrasies in institution-ally underdeveloped countries, managers of MNCsmust either forge indirect ties with institutionsby partnering local firms (Beamish, 1993; Chan

and Makino, 2007; Delios and Beamish., 1999;Henisz, 2004; Hennart, 1988; Hill, Hwang, andKim, 1990; Kim and Hwang, 1992; Makino et al.,2007; Rodriguez et al., 2005; Shan and Hamilton,1991; Vernon, 1983) or establish direct relation-ship networks with government officials or otherfirms (Guillen, 2000; Khanna and Palepu, 2000a,2000b; Khanna and Rivkin, 2001; Peng and Heath,1996; Peng and Luo, 2000; Perotti and Gelfer,2001). Such considerations are of particular impor-tance for firms investing in emerging economies, asour evidence reveals that foreign affiliates in sucheconomies are characterized as high-risk and low-return investments. Managers of MNCs shouldrecognize that the rules of the game and the capa-bilities required to survive in emerging economiessignificantly differ from those needed in advancedeconomies.

The main implication for policymakers is thatadvancing the process of institutional develop-ment serves to attract inward foreign investment.MNCs may perceive a greater investment risk inless-developed countries, because underdevelopedinstitutions have a strong impact on the varia-tion in foreign affiliate performance. To reducethe perceived risk of investment, policymakersshould therefore seek to establish stable tradingagreements, investment regulations, and economicpolicies. In addition, foreign investors may befrom home countries that are socially and cul-turally distinct from the host country (Cosset andRoy, 1991; Erb, Harvey, and Viskanta, 1996; Ghe-mawat, 2001; Habib and Zurawicki, 2002; Hymer,1960/1976; Oetzel, Bettis, and Zenner, 2001). Pol-icymakers should therefore seek to ensure thatsuch cultural and social distances do not constitutea major obstacle to inward foreign direct invest-ment. In sum, host country governments shouldactively advance the development of their institu-tions. By so doing, they will not only attract theinvestment of foreign firms, but will also improvethe long-term growth of the national economy,because transferring skills and knowledge fromforeign firms through inward investment may beless difficult and less costly than developing themfrom scratch.

Limitations

Our study has three limitations that suggest someintriguing avenues for future theoretical and empir-ical refinement. The first limitation relates to the



generalizability of our findings. Using a sample ofJapanese foreign affiliates, we find that the level ofinstitutional development of a host country influ-ences the variation in the performance of foreignaffiliates in that country. A reasonable questionthat arises from this result is whether the perfor-mance implications are specific to Japanese foreignaffiliates, especially given that Japanese foreignaffiliates have long dominated the markets in thenewly industrialized Asian countries. This issueprovides an opportunity for future researchers tochoose other organizational populations of foreignaffiliates, and to examine whether the findings ofthis study can be generalized beyond the contextof Japan.

Another potential limitation of the study lies inthe short observation period. It would be inter-esting to examine how the performance distribu-tion in Figure 1 changes over a more extendedperiod, and the extent to which such changes areattributable to changes in institutional develop-ment. Our study implicitly assumes that a hostcountry’s institutional environment is relativelystable over time because institutional change ispath-dependent and incremental (North, 1990).However, in some transition economies institu-tional change can be discontinuous and drastic(Chung and Beamish, 2005; Hitt et al., 2004; Peng,2003). Future studies could therefore focus on tran-sition economies in which institutional changeshave occurred on a large scale to investigatehow the performance of foreign affiliates variesbefore and after drastic institutional transforma-tion.

The longitudinal measures of institutional devel-opment are another area of concern. Our studyrelies on several published sources, such as theWorld Competitiveness Yearbook (1996–2001),International Monetary Fund (1996–2001), Free-dom House (1996–2001), and the InternationalCountry Risk Guide (1996–2001), to develop mea-sures of institutional development. Although thevalidity of these datasets has been examined in sev-eral studies (Gelos and Wei, 2005), they may con-tain sampling, rating, or measurement biases. Fur-thermore, the available information for the rangeof host countries included in our longitudinal anal-ysis is quite limited, and future researchers aretherefore urged to develop more comprehensivelongitudinal measures of the institutional develop-ment of host countries.

ACKNOWLEDGEMENTS

The authors would like to thank Editor WillMitchell and two anonymous reviewers for theirconstructive comments. We also thank ProfessorSir James Mirrlees, 1996 Nobel Laureate in Eco-nomic Sciences, and Professor Haruo Horaguchifor their encouragements and comments on an ear-lier draft of our article. Earlier versions of thearticle were presented at the Hong Kong Univer-sity of Science and Technology, the InternationalResearch Center for Japanese Studies symposium,a Japan Academy of International Business Stud-ies meeting, an Academy of Management meeting,and an Academy of International Business meet-ing. We thank the participants of these symposiumsand meetings for their valuable feedback. Thisstudy was supported by a grant from the ResearchGrants Council of the Hong Kong Special Admin-istrative Region (Project No. HKU 741207H).

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APPENDIX I. MEASURES OF INSTITUTIONAL DEVELOPMENT

Variables Descriptions

Economic institutionsGDP per capita (in U.S. dollars) Log of gross domestic product (GDP) per capita at current prices and exchange

rates.Source: International Monetary Fund 1996–2001.

Economic conditions The extent to which a country has well-developed economic systems. Scaled from1 to 12, with a higher score indicating greater desirability for MNCs.

Source: International Country Risk Guide 1996–2001.Distribution infrastructure The extent to which the distribution infrastructure for goods and services in a

country is generally efficient. Scaled from 1 to 10, with a higher scoreindicating greater desirability for MNCs.

Source: World Competitiveness Yearbook 1996–2001.Financial resources The extent to which credit flows easily from banks to businesses. Scaled from 1

to 10, with a higher score indicating greater desirability for MNCs.Source: World Competitiveness Yearbook 1996–2001.

Political institutionsIntellectual property rights The extent to which patent and copyright protection are enforced in a country.

Scaled from 1 to 10, with a higher score indicating greater desirability forMNCs.

Source: World Competitiveness Yearbook 1996–2001.Political system The extent to which the political system is well adapted to today’s economic

challenges. Scaled from 1 to 10, with a higher score indicating greaterdesirability for MNCs.

Source: World Competitiveness Yearbook 1996–2001.Law and order The strength and impartiality of the legal system. Scaled from 0 to 10, with a

higher score indicating a lower risk and thus greater desirability for MNCs.Source: International Country Risk Guide 1996–2001.

Bureaucracy quality The extent to which the institutional strength and quality of the bureaucracyminimize revisions in policy when governments change. Scaled from 0 to 10,with a higher score indicating greater efficiency and thus greater desirability forMNCs.

Source: International Country Risk Guide 1996–2001.

Social institutionsJustice The extent to which justice is fairly administered in society. Scaled from 1 to 10,

with a higher score indicating greater desirability for MNCs.Source: World Competitiveness Yearbook 1996–2001.

Harassment and violence The extent to which harassment and violence seriously destabilize the workplace.Scaled from 1 to 10, with a higher score indicating greater desirability forMNCs.

Source: World Competitiveness Yearbook 1997–2001.Corruption in government The extent to which corruption within the political system is likely to occur.

Scaled from 0 to 10, with a lower score indicating severe corruption and thuslesser desirability for MNCs.

Source: International Country Risk Guide 1996–2001.Civil freedom The extent to which a country guarantees freedom of expression, assembly,

association, and religion. Scaled from 1 to 7, with a lower score indicatingmore freedom.

Source: Freedom House 1996–2001.

APPENDIX II. INSTITUTIONAL DEVELOPMENT INDEX (IDI)

Country 1996 1997 1998 1999 2000 2001 Average

Argentina −1.041 −0.854 −0.889 −0.766 −0.814 −0.988 −0.892Australia 0.877 0.989 1.083 1.145 1.205 1.188 1.081Austria 0.919 0.781 0.827 0.921 0.980 1.102 0.922Belgium 0.589 0.108 0.139 0.221 0.363 0.472 0.315



APPENDIX II. (Continued )

Country 1996 1997 1998 1999 2000 2001 Average

Brazil −1.296 −0.991 −1.096 −1.280 −1.096 −0.924 −1.114Canada 1.053 1.120 1.270 1.189 1.153 1.166 1.158Chile 0.057 −0.097 −0.217 −0.035 −0.104 0.017 −0.063China −1.453 −1.349 −1.114 −1.045 −1.233 −1.383 −1.263Colombia −1.492 −1.909 −1.749 −1.595 −1.847 −1.679 −1.712Czech Republic −0.453 −0.566 −0.503 −0.709 −0.641 −0.515 −0.565Denmark 1.333 1.455 1.458 1.447 1.401 1.308 1.400Finland 1.012 1.241 1.313 1.364 1.442 1.441 1.302France 0.358 0.300 0.352 0.450 0.482 0.295 0.373Germany 0.848 0.937 0.836 0.917 0.954 0.872 0.894Greece −0.311 −0.344 −0.417 −0.371 −0.416 −0.271 −0.355Hong Kong 0.796 0.669 0.481 0.233 0.120 0.327 0.438Hungary −0.361 −0.311 −0.080 0.014 −0.001 −0.192 −0.155Iceland 0.833 0.896 0.989 0.908 0.953 0.887 0.911India −1.212 −1.418 −1.122 −1.113 −1.119 −1.163 −1.191Indonesia −1.254 −1.372 −1.669 −1.870 −1.608 −1.913 −1.614Ireland 0.778 0.774 0.836 0.791 0.745 0.844 0.795Israel 0.589 0.164 0.185 0.224 0.218 0.316 0.283Italy −0.474 −0.435 −0.332 −0.336 −0.407 −0.398 −0.397Japan 0.512 0.509 −0.092 0.090 0.227 0.177 0.237Luxembourg 1.284 1.223 1.204 1.229 1.133 1.269 1.224Malaysia 0.001 0.085 −0.105 −0.455 −0.595 −0.773 −0.307Mexico −1.717 −1.484 −1.222 −1.185 −0.992 −0.842 −1.240Netherlands 1.030 1.138 1.221 1.216 1.292 1.262 1.193New Zealand 1.113 1.310 1.041 0.919 0.882 0.909 1.029Norway 1.164 1.175 1.184 0.898 0.907 0.750 1.013Philippines −1.321 −1.069 −0.938 −0.773 −1.157 −1.334 −1.098Poland −0.560 −0.667 −0.563 −0.627 −0.612 −0.733 −0.627Portugal −0.064 −0.029 0.171 0.291 0.047 0.069 0.081Russia −2.190 −1.842 −1.843 −2.251 −2.106 −1.830 −2.010Singapore 0.989 0.976 1.058 1.031 1.032 0.961 1.008South Africa −0.157 −0.338 −0.528 −0.572 −0.571 −0.575 −0.457South Korea −0.284 −0.625 −0.869 −0.776 −0.519 −0.533 −0.601Spain −0.138 0.097 0.006 0.282 0.215 0.227 0.115Sweden 0.923 0.878 1.003 1.077 0.980 1.072 0.989Switzerland 1.079 1.196 1.040 1.019 1.048 1.156 1.090Taiwan 0.004 −0.281 −0.032 0.011 −0.200 −0.258 −0.126Thailand −0.747 −0.737 −1.232 −0.957 −0.972 −0.859 −0.917Turkey −1.288 −1.363 −1.417 −1.351 −1.185 −1.298 −1.317United Kingdom 0.617 0.747 0.852 0.748 0.913 0.749 0.771United States 0.880 0.993 1.114 1.009 1.135 1.145 1.046Venezuela −1.826 −1.679 −1.637 −1.577 −1.630 −1.518 −1.645

Note. The IDI scores are calculated by using the principal component method. The averages and standard deviations in each year are0 and 1, respectively

APPENDIX III. CORRELATIONS BETWEEN THE IDI AND OTHER INSTITUTIONAL MEASURES

Institutional Measures Data source Items Year1 N Correlationcoefficients2

Economic institutionsGlobal

CompetitivenessRanking (2006)

World EconomicForum

Institutions, infrastructure, macro-economy,health and primary education, highereducation and training, market efficiency,technological readiness, businesssophistication, innovation.

2006 46 0.806



APPENDIX III. (Continued )

Institutional Measures Data source Items Year1 N Correlationcoefficients2

PotentialCompetitivenessRanking (2000)

Japan Center forEconomic Research

Internationalization, enterprise,education, finance,government, science andtechnology, infrastructure,information technology.

2000 43 0.856

IT IndustryCompetitiveness

Economist IntelligenceUnit, The Economist

Business environment, ITinfrastructure, human capital,legal environment, R&Denvironment, support for ITindustry development.

1996–2001 44 0.787

Productivity Ranking(human capital)

OECD Education and human capital. 1996–2001 32 0.821

Productivity Ranking(public infrastructurecapital)

OECD Public infrastructure capital. 1996–2001 32 0.763

Productivity Ranking(worker productivityin manufacturing)

OECD Worker productivity inmanufacturing.

1996–2001 32 0.701

Stock MarketDevelopment Index I

World Bank Aggregate information onmarket capitalization, totalvalue traded/GDP, andturnover.

1996–2001 39 0.570

Stock MarketDevelopment Index II

World Bank APT pricing-error estimates. 1996–2001 18 0.836

Stock MarketDevelopment Index III

World Bank ICAPM pricing-error estimates. 1996–2001 39 0.758

Political institutionsVoice and accountability World Bank World Development Indicators:

Voice and accountability.1996–2000 46 0.767–0.824

Political stability World Bank World Development Indicators:Political stability.

1996–2000 46 0.818–0.869

Governmenteffectiveness

World Bank World Development Indicators:Government effectiveness.

1996–2000 46 0.950–0.975

Regulatory quality World Bank World Development Indicators:Regulatory quality.

1996–2000 46 0.795–0.937

Rule of law World Bank World Development Indicators:Rule of law.

1996–2000 46 0.957–0.966

Control of corruption World Bank World Development Indicators:Control of corruption.

1996–2000 46 0.967–0.979

TransparencyInternationalCorruption PerceptionsIndex (2000)

Internet Center forCorruption Research

Corruption. 2000 46 0.968



APPENDIX III. (Continued )

Institutional measures Data source Items Year1 N CorrelationCoefficients2

Social institutionsTrust (1990–1991) The World Values

SurveyThrift, determination, hard

work, obedience, religiousfaith, respect, associationalrelationships, trust.

1990–1991 28 0.789

Human DevelopmentIndex

UNDP Life expectancy index,education index, GDP index.

1996–2001 46 0.790–0.830

Heritage FoundationIndex of EconomicFreedom

Heritage Foundation Business freedom, laborfreedom, trade freedom,fiscal freedom, monetaryfreedom, investmentfreedom, financial freedom,freedom from corruption,freedom from government,property rights.

1996–2001 46 0.783–0.855

Quality-of-life Index(2005)

EconomistIntelligence Unit,The Economist

Material well being, health,political stability andsecurity, family life,community life, climate andgeography, job security,political freedom, genderequality.

2005 46 0.831

Software Piracy Rate(2003)

Business SoftwareAlliance

Intellectual property protection,pirated software, culturaldifferences.

2003 44 −0.858

1 Where the data sources provided the information on the items in specific years between 1996 and 2001, correlation analyses wereconducted for each year separately using the IDI for the corresponding year. Otherwise, the average IDI was used for the correlationanalyses.2 All of the coefficients are significant at the p < 0.001 level

APPENDIX IV. LEVEL OF AND VARIATION IN ROS IN HOST COUNTRIES

Country Code No. ofaffiliates

Level ofROS

(mean)

Variationin ROS

Country Code No. ofaffiliates

Level ofROS

(mean)

Variationin ROS

Argentina ARG 20 −0.8218 10.0720 Malaysia MYS 363 2.5907 7.1990Australia AUS 211 2.0751 7.1679 Mexico MEX 81 2.4169 7.6407Austria AUT 23 0.6201 2.5154 Netherlands NLD 138 1.4495 4.7314Belgium BEL 73 1.8352 3.7891 New Zealand NZL 44 1.7670 4.6996Brazil BRA 113 1.8324 10.2728 Panama PAN 83 2.3806 7.3999Canada CAN 152 2.0415 4.2433 Peru PER 12 0.3827 5.0652Chile CHL 23 1.6314 7.3898 Philippines PHL 151 1.5847 7.9936China CHN 727 1.1108 9.2232 Poland POL 15 1.2724 3.8251Denmark DNK 12 1.5346 2.4519 Portugal PRT 14 2.6165 3.9945France FRA 160 1.0413 3.9613 Russia RUS 12 −0.9824 9.9458Germany DEU 299 1.0316 3.1691 Singapore SGP 468 1.7586 4.9756Great Britain GBR 356 0.6201 5.6432 Spain ESP 74 2.8958 4.9180Hong Kong HKG 437 1.5447 5.3302 Sweden SWE 29 1.7685 2.1103Hungary HUN 12 1.8206 2.7223 Switzerland CHE 27 2.7418 3.5383India IND 52 1.5349 6.5036 Taiwan TWN 403 3.2029 4.8173Indonesia IDN 281 1.5003 15.0626 Thailand THA 479 1.1501 12.6701Italy ITA 84 1.3305 3.0922 United States USA 1,464 1.1795 5.8325Korea (South) KOR 215 3.9643 6.5120 Venezuela VEN 12 −1.9610 9.0088Liberia LBR 14 3.7077 13.5333 Vietnam VNM 39 −2.0219 14.0789


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