Ethnic Chinese Networking in Cross-border Investment: The Impact of Economic and Institutional Development. Abstract:

Transcription

1 Ethnc Chnese Networkng n Cross-border Investment: The Impact of Economc and Insttutonal Development Sarah Y. Tong * Hong Kong Insttute of Economcs and Busness Strateges The Unversty of Hong Kong Aprl 2003 Abstract: Ethnc Chnese entrepreneurs are known for ther actve domestc and cross-border busness networkng practces, partcularly n Southeast Asa. Ths paper emprcally nvestgates the role of ethnc Chnese networks n promotng foregn drect nvestment (FDI). Usng a standard gravty model to analyze blateral FDI reported by 54 economes, we fnd that ethnc Chnese networks are mportant n facltatng cross-border drect nvestment between countres. The strength of ethnc Chnese networks between country pars, approxmated by the product of the numbers of ethnc Chnese n both countres, s postvely correlated wth the cumulatve amount of ther recprocal FDI. More mportantly, ths sgnfcant relatonshp s not lmted to countres n Southeast Asa, but s applcable to other country pars ncluded n the study as well, regardless of whether the nvestment orgnated from ndustral countres or developng economes. Fnally, the analyss fnds no evdence that ethnc networks are only effectve n countres where economc and legal nsttutons are under-developed. The measure for ethnc Chnese networks s found sgnfcant n promotng FDI to countres wth a relatvely hgher bureaucratc qualty, and the magntude of the coeffcent s n fact much larger than that found for FDI destned to countres wth a lower bureaucratc qualty. * The author wshes to thank James Rauch for hs many encouragng and helpful suggestons. She also thanks Vtor Trndade for hs assstant n complng part of the data. Dudley Poston L. Jr. kndly provded data on ethnc Chnese populaton.

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3 I. Introducton The mportance of busness and socal networks n facltatng trade has been the focus of many recent studes, from both the theoretcal (Gref, 1993; Rauch & Casella, 1998) and emprcal aspects (Gould, 1994; Balderbos & Sleuwaegen, 1998; Rauch & Trndade 2002). Theoretcal analyses pont out that networkng actvtes are key n overcomng nformatonal barrers n nternatonal transactons, such as nadequate nformaton about nternatonal trade opportuntes and the qualty of potental busness counterparts abroad, and also provde communty enforcement sanctons to deter volatons of contracts n a weak nternatonal legal envronment. Emprcal analyses show that networks sgnfcantly ncrease blateral trade, especally trade n dfferentated goods (Rauch and Trndade, 2002), suggestng that networkng actvtes are key n formng a match between buyers and sellers where complex nformaton s needed. The role of networks n promotng cross border nvestment has not yet been studed extensvely. As an mportant form of nternatonal economc actvty, foregn drect nvestment requres large startng costs and ntensve nformaton. It entals searchng for potental locatons, conductng feasblty studes, obtanng government approval, buldng factores, nstallng machnery and equpment, and hrng workers. Compared to trade, FDI calls for cooperaton and commtment at a much deeper level between the partes concerned, and therefore encounters a hgher nformatonal barrer. It s therefore reasonable to expect that ethnc networks play a more mportant role n assstng blateral FDI than n encouragng trade. There are varous types of busness and socal networks. Coethnc networks have tended to attract emprcal research, snce t s much easer to dentfy ther members, and 3

4 several studes on such groups have been made n recent years (e.g. Kotkn, 1992; Wedenbaum & Hughes, 1996; Lght & Isralowtz, 1997). Overseas Chnese 1 have the most well-known ethnc networks actve n trade and n drect nvestment (Reddng, 1995). The vgorous networkng actvty among ethnc Chnese n Southeast Asa and ther commercal success have both been hghly vsble, and these networks are beleved by many to have played a crucal role n some of the regon s fast growth n recent decades. Lke many other ethnc groups lvng outsde ther countres of orgn, overseas Chnese create varous formal or nformal assocatons. These assocatons have tradtonally been based on knshp, dalect and place of orgn n Chna, and were establshed partly to provde assstance to those n need n the communty, especally new mmgrants. As an ethnc Chnese communty becomes more commercally developed, these assocatons begn serve as centers where nformaton exchange takes place between coethnc busness people workng both locally and n other parts of the world. It s possble to consder overseas Chnese as formng a set of nter-connected networks at varous local and natonal levels, especally n Southeast Asa, but not a unfed nternatonal system. In recent years, however, there have been sgns that the nternatonal lnks have been formalzed n organzaton, perhaps strengthened n capacty, and extended to other parts of the world outsde Southeast Asa (Lu 1998, EAAU 1995). Ths paper contrbutes to the lterature by emprcally nvestgatng the mpact of ethnc Chnese networks on promotng blateral FDI. We wll concentrate manly on three ssues. Frst, do ethnc Chnese networks sgnfcantly ncrease the cumulatve amount of FDI between countres? The answer to ths queston s mportant to governments n 1 The term Overseas Chnese n ths paper refers to ethnc Chnese resdng outsde manland Chna and Tawan. 4

5 formulatng polces. For example, polces encouragng cooperaton between ethnc mnortes and ther overseas counterparts may generate sgnfcant benefts to a country s long-term growth. Second, s the mportance of ethnc Chnese networks specfc to Southeast Asan economes? Ths s also a queston wth mportant mplcatons. If ethnc Chnese networks are found to be mportant for blateral FDI outsde Southeast Asa, t suggests that networks of other ethnc groups could also play a sgnfcant role n facltatng cross-border nvestment actvtes. Thrd, s the effectveness of ethnc Chnese networks on FDI condtonal on a low level of nsttutonal development n the host countres? If so, then lttle attenton need be pad to the ssue, as only a small percentage of FDI s destned to countres where economc and legal nsttutons are under-developed. In the next secton, we specfy our emprcal model and dscuss the varables used n the estmaton. Secton IV descrbes the data and specfes the measures. We present our results and dscuss the mplcatons n Secton V. Secton VI provdes some concludng remarks. II. Emprcal Model A. Gravty model specfcaton In ths study, we examne the effects of ethnc Chnese networkng on blateral FDI usng the gravty specfcaton, whch s wdely used n trade lterature. The basc gravty model states that the total amount of trade between two countres s drectly related to the product of ther economc masses (measured by ether GDP or GNP) and nversely related to the dstance between them. Per capta ncome s also often ncluded n gravty models (Eaton and Tamura, 1994; Rauch and Trndade 2002). Gravty models have attracted 5

6 wdespread attenton because of ther emprcal success n predctng blateral trade volumes. Recent theoretcal works (e.g. Anderson, 1979; Bergstrand, 1985, 1989; Helpman, 1987; and Deardorff, 1995) show that gravty specfcaton s consstent wth varous trade models. In addton to the basc elements, varous factors that ether ad or deter trade are also ncluded n the standard gravty models. It s assumed that these factors wll cause blateral trade to devate somewhat from the basc proportonal relatonshp. For example, dummy varables are ncluded to ndcate specal relatons between the two tradng countres, such as a former colonal relatonshp, a common natve language, geographcal proxmty, and common membershp of a tradng bloc (Frankel 1997; Rauch and Trndade 2002). Recent studes have employed gravty models to predct the amount of FDI (Eaton and Tamura, 1994; Jeon and Stone, 1998; Morsnk 1998; We 1998). Morsnk, for example, developed an emprcal specfcaton to analyze FDI, smlar to gravty models used to predct blateral trade, based on the theory of nternatonal producton and theores on localzaton strateges. The model ncorporated factors thought to affect frms nvestment decsons, categorzng them as push factors, pull factors, stmulus factors and frcton factors. Many of the varables are smlar to those often used n the trade models, such as total market sze of the host country, per capta ncome, labor cost, and cultural dfferences. The use of the gravty model to estmate foregn drect nvestment mples the vew that trade and foregn nvestment, to a large extent, complement each other. Standard trade models would predct that trade and nternatonal producton factor moblty are substtutes 6

7 (e.g. Mundell 1957). Emprcal studes, however, have shown that more often than not, trade and nternatonal factor moblty complement each other (Lpsey and Wess, 1981; Collns, O Rourke & Wllamson, 1997; Jeon & Stone, 1998; Head & Res, 2001; Heaz & Safaran, 2001). To consder emprcally the queston of complementarty between trade and drect nvestment, we nclude n the model a measure of a host country s overall trade ntensty. Theoretcal models establshed by authors such as Helpman and Markusen (Helpman 1984, 1985; Markusen 1995) emphasze the role of multnatonal corporatons and ther frm specfc assets. They also generate testable mplcatons for the locaton of nvestment. For example, ndustral countres, where sklled labor s relatvely abundant, should be the domnant source countres for multnatonals. Large countres, especally those wth a large unsklled labor force, may be the domnant host countres for multnatonals. In addton, these models suggest that the effect of trade barrers on drect nvestment may depend on the type of nvestment. On the one hand, hgh trade barrers encourage horzontal drect nvestment 2 between large ndustral countres where countres are smlar n sze and n relatve endowments. On the other hand, they dscourage vertcal drect nvestment between ndustral countres and developng countres where relatve endowments are unbalanced. In our emprcal models, the GNP and per capta GNP of the source and the host countres could be seen as measures of a country s sze and relatve endowment wth sklled labor. Moreover, measures on the level of host countres trade barrers are also ncluded n the model. 2 Horzontal drect nvestment means the foregn producton of products and servces roughly smlar to those the frm produces for ts home market, whle vertcal nvestment nvolves the fragmentaton of the producton process geographcally by stages of producton. 7

8 Compared to ther counterparts n ndustral countres, multnatonal corporatons n developng countres generally possess less frm specfc advantages. Normally, for example, they have fewer resources avalable for R&D actvtes. FDI from developng countres, therefore, may respond to the varables dfferently. Our emprcal analyss wll address the queston by estmatng equatons separately for FDI orgnatng from ndustral and developng countres respectvely. B. Ethnc Chnese Networks The man purpose of ths paper s to nvestgate the sgnfcance of ethnc Chnese networks n facltatng blateral foregn drect nvestment. Earler work has suggested two maor mechansms whereby coethnc networks promote nternatonal busness transactons such as trade and nvestment. One mechansm, establshed by Gref (1989, 1993), s that coethnc networks provde communty enforcement of sanctons to deter volatons of contracts n a weak nternatonal legal envronment. An alternatve mechansm, emphaszed n more recent work by Gould (1994) and Rauch and Casella (1998), s that coethnc networks promote FDI by provdng foregn nvestors wth mportant nformaton that may otherwse be dffcult or costly obtan, n respect of the domestc market, local government regulatons, and potental busness partners. Both these mechansms seem to be consstent wth descrptons of the operaton of ethnc Chnese networks (see, for example, Wedenbaum and Huges, 1996). It s, however, dffcult to dstngush the two mechansms emprcally n our study. It seems reasonable to assume that ethnc networks are more mportant n communty enforcement of sanctons where the FDI s destned to countres wth weak rather than strong nsttutons. As for the role played by ethnc networks n provdng nformaton, t s dffcult to udge. On the one 8

9 hand, less nformaton s avalable publcly n countres wth weak nsttutons, enhancng the value of that provded through ethnc networks. On the other hand, ethnc networks mght be more effcent wth strong nsttutons when there s more transparency n the bureaucratc system. To get some deas of the two mechansms relatve mportance, we dvde the FDI data nto two groups estmate the gravty model separately. The frst group ncludes FDI destned to countres wth weak nsttutons and the second ncludes FDI destned to countres wth strong nsttutons. C. Introducton of the Varables Followng the usual gravty model specfcatons, we nclude the total GNPs of the both the source country and the host country, as well as the dstance between the two. We could thnk of the source country s GNP as an ndcaton of the country s potental supply of FDI. The host country s total GNP ndcates the country s potental demand for FDI. We expect the above two to have a postve nfluence on total FDI, whle the dstance between the two s expected to carry a negatve sgn. We also nclude a country s GNP growth rate to capture the mpact of a country s market growth on ts nward FDI. Unlke other studes, we nclude the total populatons of the source and the host countres nstead of per capta GNPs. Frst of all, combnng GNP and populaton can produce equvalent measures for the effect of per capta ncomes. The more mportant reason s the followng. As wll be explaned later, the numbers of ethnc Chnese wll be ncluded n the model. It s qute possble that the number of ethnc Chnese n a country s correlated wth ts populaton. Includng total populaton n the analyss wll exclude the possble effect of populaton on FDI. 9

10 Besde the basc factors, addtonal varables are ncluded to reflect ther possble role n ether mpedng or assstng FDI between countres. One such factor s whether two countres are adacent wth each other. Studes suggest that there are advantages n tradng wth neghborng countres and we examne whether sharng a common border may also have an addtonal postve mpact on FDI. Studes also ndcate that regonal tradng blocs affect the blateral FDI of the member states. Two dummy varables, EEC and EFTA, are added to ndcate membershp n the European Communty and the European Free Trade Assocaton, both of whch were actve at the tme when FDI was reported. The model also ncludes a varable ndcatng whether two countres have former colonal tes, whch may provde nvestors wth advantages n terms of a relatvely famlar socal and poltcal envronment. It may also capture the effect of some wdely used second language or offcal language n many former colones. Fnally, studes suggest that country pars remotely located from the rest of the world tend to have closer trade relatons (Deardorff 1998; We, 1996, and Rauch and Trndade 2002). We nclude the host country s trade ntensty and barrers to trade n our emprcal model. Trade ntensty s ncluded to explore the relaton between trade and FDI and s represented by a country s rato of total trade to GDP. By ncludng a measure on barrers to trade, we can assess whether tarff umpng s an mportant motvaton for FDI. In addton, as hgh tarffs have been held to ncrease horzontal FDI and decrease vertcal FDI, we can also use ths measure to examne the relatve mportance of the two types of FDI. To examne the mpact of ethnc Chnese networks on blateral FDI, we add the product of the numbers of ethnc Chnese n the source and the host countres nto the 10

11 emprcal model. It s a proxy of the strength of ethnc Chnese networks between two countres and could be nterpreted as the total number of potental connectons between the ethnc Chnese populatons n the two countres. 3 One concern s that our measure could have possbly captured a common language effect. Clearly, t s much easer for people speakng the same language to communcate and to make busness deals. In addton, a shared mother tongue often mples smlar cultural and socal values. It s partcularly mportant to recognze the effect of a common language when studyng the role of ethnc Chnese. Many ethnc Chnese, especally those n Southeast Asa, share one or more dalects, ncludng Hokken, Teochu, Cantonese, and Hakka. Wthout consderng the common language factor, t s debatable whether a postve effect of our measure on ethnc Chnese networks s n fact attrbutable to the networkng. In the emprcal model, we nclude a varable measurng the extent to whch two countres share a common natve language. D. Basc emprcal model follows: Based on these prncples, we can now wrte out our basc gravty model as where FDI = αgnp * TAR τ 2 β1 GNP TRADE β 2 ρ2 + λlanguage POP γ 1 CHIN POP ψ γ 2 exp( ξadj + ϕcolotie DIST δ * REM + ηeec 2 ε REM ε 2 + θefta + ω GROGDP + µ ) (1) Subscrpts 1 and 2 denote the coeffcents for the source country and host country; 3 Alternatvely, we could use the product of the ethnc Chnese share of the total populaton of the two countres. That measure could be seen as the probablty that, f we select an ndvdual at random from each country, both wll be ethnc Chnese. The two measures are related but the coeffcents wll ental dfferent nferences. 11

12 FDI denotes the nomnal value of total FDI stock from country to country ; GNP,GNP denote the nomnal GNPs of country and country n 1990; POP, POP denote the total populatons n country and country n 1990; DIST equals the great crcle dstance 5 between the prncpal ctes (economc centers) of country and country ; REM, REM are the weghted sum of country s and country s dstances from all other countres n the sample. The weghts are the nomnal GNPs of the other countres n the sample; ADJ equals 1 f country and country share a land border and 0 otherwse; EEC equals 1 f countres and are both members of the European Communty and 0 otherwse. EFTA equals 1 f countres and are both members of the European Free Trade Assocaton and 0 otherwse. LANGUAGE s a measures of the extent to whch countres and share brth languages; COLOTIE equals 1 when and share a former colonal te and 0 otherwse; TAR s the host country s average tarff rate for the years 1985 to 1990; TRADE s the host country s average trade to GDP rato for the years 1985 to 1990; GRPGDP s the host country s annual average GDP growth rate between 1985 and 1990; 4 As wll be explaned n the next secton, FDI stocks for some host countres are not avalable for The avalable fgure for a year that s closest to 1990 s used nstead. A varable ndcates that the year that the data s reported s therefore also ncluded n the estmaton. 5 The formula used to calculate great crcle dstances between prncpal ctes s explaned brefly n the Appendx. 12

13 CHIN s the product of the numbers of ethnc Chnese n country and country n 1990; 6 µ s a Gaussan whte nose error term assocated wth FDI. The dependent varable, FDI, s non-negatve and thus bounded below by zero. Followng Eaton and Tamura (1994) we estmate a modfed gravty model, also called the threshold gravty model, as t assumes that the actual FDI wll be strctly postve only when the rght-hand sde of the equaton acheves a mnmum threshold value A. The gravty model to be estmated s thus FDI = max[ A + αgnp β1 GNP β2 POP γ 1 POP γ 2 DIST δ REM ε REM ε 2 * TAR τ 2 TRADE ρ2 + λlanguage CHIN ψ exp( ξadj + ϕcolotie + ηeec 2 + θefta + ω GROGDP + µ ), 0] (2) Rearrangng and takng natural logarthms of both sdes yelds ln( A + FDI ) = max[ln α + β 1 ln GNP + β 2 GNP + γ 1 ln POP + γ 2 ln POP + δ ln DIST + ρ 2 ln TRADE + λlanguage + ε ln REM 1 + ψ ln CHIN + ε + ϕcolotie 2 ln REM + ξadj 2 + τ 2 + ηeec ln TAR + ω GROGDP + µ + θefta ), lna] (3) Equaton (3) s estmated usng the maxmum lkelhood method, where the lkelhood functon s constructed usng a threshold Tobt model. The detaled estmaton procedures can be found n Eaton and Tamura (1994). E. FDI nvolvng Southeast Asan economes To convncngly account for the mpact of ethnc Chnese networks n promotng FDI, we should recognze the unque and mportant role of ethnc Chnese n Southeast Asa. There are an estmated nearly 37 mllon ethnc Chnese lvng outsde manland 6 When we estmate separately the coeffcents for the number of ethnc Chnese n both the source and host 13

14 Chna and Tawan. Nearly 90 percent of them resde n Southeast Asa. The presence of ethnc Chnese n many Southeast Asan economes s not only substantal but also economcally sgnfcant. In addton, unlke other regons n the world, the ethnc Chnese networks n Southeast Asa have a long hstory and are well-establshed. Thus, we mght expect the nfluence of ethnc Chnese on FDI to be stronger wthn the Southeast Asan regon than n other parts of the world. To dentfy dfferences n the mportance of ethnc Chnese networks, we estmate three coeffcents on ethnc Chnese networkng, one for country pars where both are n Southeast Asa, one for country pars where ether the source or the host country s n Southeast Asa, and one for the country pars whether nether s n Southeast Asa. Another concern s the possble mpact on the estmaton results on ethnc Chnese networks f nvestment n Chna s ncluded. Overseas Chnese have played an essental role n nvestng n Chna. For example, untl recently, the maorty of FDI n Chna orgnated from neghborng Southeast Asan economes where ethnc Chnese account for a sgnfcant fracton of ther economes. In addton, wthn Chna, FDI s concentrated n Guangdong and Fuan, the two southeastern provnces that are home for most ethnc Chnese outsde manland Chna and Tawan. One could argue that nvestment by overseas Chnese n Chna may not be motvated by economc nterests, and that the results could be msleadng f these nvestments are ncluded n the analyss. In our emprcal analyss, our model s re-estmated excludng FDI to Chna, and smlar results are obtaned. 7 countres, a statstcal test ndcates that we cannot reect the hypothess that the two estmates are the same. 7 Estmaton results excludng FDI to Chna are obtaned but not reported, due to space consderatons. A related ssue concerns nvestments n manland Chna, Tawan and Hong Kong. Because of hstorc poltcal crcumstances, nvestment between Tawan and manland Chna s prohbted offcally and thus mostly channeled through Hong Kong. In addton, there s also the phenomenon of round-trppng nvestment, where nvestments n manland Chna ostensbly from Hong Kong n fact orgnate wthn manland Chna, 14

15 III. Data and Measurement The sample ncludes 70 countres (Table 1). 8 These nclude 16 countres n North and South Amerca, 11 n East and Southeast Asa, 14 n Afrca, 5 n West Asa, 4 n Oceana, 15 n Western Europe, and 5 n Eastern Europe. Of the ffteen Western European countres, 10 were member countres of the EEC and 5 members of EFTA. For each of the country pars, the great crcle dstances between ther economc centers were calculated usng the formula explaned brefly n Appendx B. Data for GNP n current dollars were obtaned from the IMF Internatonal Fnancal Statstcs for Informaton used to construct the varable on adacency was obtaned from the web page for Emprcal Investgaton n Internatonal Trade (EIIT, European Communty membershp and European Free Trade Assocaton membershp are from Frankel (1997). The varable for colonal tes was constructed on the bass of artcles n the Encyclopeda Brtannca (1997). Data on the countres unweghted average tarff rates between 1985 and 1990 came from the World Development Indcators 2000 (World Bank, 2000). The countres trade to GDP rato and ther GDP values n constant dollars for the years 1985 and 1990 also came from the World Development Indcators. The latter was used to calculate ts GDP growth rate. Most of the data on ethnc Chnese populatons came from Poston (1994). Supplementary nformaton was obtaned from the Overseas Chnese Economy Yearbook 1990 and Tao (1994). Three language varables were constructed to account for the effect of a common natve language between countres. The smplest of the three measures s a but were channeled through Hong Kong n order to beneft from preferental tax arrangements. To remove possble dstortons, nvestment wthn these three economes s excluded from the analyss. 15

16 dummy varable. It takes the value of 1 f at least 10% of the populatons share a common natve language and 0 otherwse. It was constructed on the bass of country artcles n the Encyclopeda Brtannca, combned wth Ethnologue (Grmes 1992). 9 Two contnuous language varables were constructed usng the formula s l s l for country par and. l s l s the share of natve speakers of language l n county and s l s the equvalent share n country. The share was obtaned by dvdng the number of natve speakers of each language obtaned from Ethnologue by the mdyear populaton estmates for the correspondng years n the Unted Natons Demographc Yearbook. In creatng one contnuous language varable, nne maor languages were ncluded (l=9), the same method as used n Rauch and Trndada (2002). In creatng the other contnuous language varable, 21 languages were used, ncludng all languages that have at least 1% natve speakers n at least two countres. Ths was done to account for the addtonal effect of some common dalects spoken by Chnese n Southeast Asa. 10 Indces on nsttutonal development for 1990 came from Internatonal Country Rsk Gude (ICRG), a monthly publcaton of Poltcal Rsk Servces. Of the fve ndces 11 provded n the orgnal data, the scores on bureaucratc qualty were thought to be the most relevant and were used to ndcate a host country s nsttutonal development. Unlke We (1998) and Morsnk (1998), who both used FDI from OECD data, we assembled blateral FDI data from the Unted Natons World Investment Drectory. The 8 The number of countres ncluded n the sample was lmted by data avalablty of FDI fgures and data on ethnc Chnese populatons. The dependent varable, as wll be explaned later, was the stock of FDI from country to country n (or around) 1990, 9 Encyclopeda Brtannca lsts maor languages spoken n each country. Ethnologue (Grmes 1992) gves the numbers of natve speakers for each of the varous languages spoken n a country. 10 Results usng alternatve languages are smlar to those usng the smple dummy language varable and thus are not reported n the paper. 16

17 advantage s that the Drectores nclude not only nvestments from OECD countres and other ndustral natons, but nvestments orgnatng from developng countres as well. Unfortunately, the Drectores contan only one volume 12 for each of the regons and were publshed n dfferent years for each regon. Even wthn the same volume, nformaton for dfferent countres dffers n the years when FDI s reported. As a result, the data obtaned for dfferent country pars are fgures for dfferent years 13. To mnmze the possble problems rsng from ths temporal nconsstency, we used the FDI stocks rather than the flows n the estmaton. Ths approach mght also be helpful n lmtng the effect of factors that cause short-term fluctuatons n yearly FDI flows. In addton, we ncluded a varable n our estmaton to ndcate the year that the amount of FDI s reported. The data on blateral FDI was gathered from the reports of 54 host countres on nward nvestment n World Investment Drectory, and these reports dentfy 69 source countres 14. If blateral FDI was reported for all the country pars, 0 or postve, there should be more than 3,600 observatons, but only 1,329 vald observatons were actually obtaned and used n the emprcal estmaton. 15 Table 2 s a summary of the data on FDI. The total FDI stock reported amounted to US$1.06 bllon. The maorty of FDI orgnated from ndustral countres (96%), and was destned to ndustral countres (83%) 16. More 11 The fve ndces are: scores on government repudaton of contracts, rsk of expropraton, corrupton, law and order tradton, and bureaucratc qualty. 12 An updated nvestment drectory on East and Southeast Asa was publshed recently. 13 For FDI stock data compled, the avalable years vary across countres, rangng from 1987 to For most of the countres n the study, the data covered FDI stock at the end of ether 1989, 1990 or The nward FDI report of El Salvador was used to comple the data, but the country s not dentfed as a FDI source by any countres. 15 There are two possbltes for the mssng observatons. Frst, there s zero nvestment between the two countres. Second, the total amount of blateral nvestment s relatvely small and therefore s not lsted n the table. In both cases, the observaton s treated as mssng. 16 The total amount of FDI used n the analyss accounts for about 60% of FDI stock n 1990 reported by UNCTAD ( The dscrepancy s probably due to multple sources. For example, ther exst dfferences n defnng FDI stocks across countres. Second, our sample ncludes nward FDI stock of only 54 countres. 17

18 than 80 percent of total FDI takes place between ndustral countres. In addton, the average blateral FDI stocks ether outward from or nward to ndustral countres are much larger than those for developng countres. Table 2 shows that the average amount of outward FDI stock from ndustral countres nvestment s around US$1.3 bllon, more than 16 tmes that for developng countres. The average quantty of nward FDI stock to ndustral countres amounts to about US$2.0 bllon, nearly 10 tmes as hgh as that for developng countres on average. IV. Results of Estmaton A. Estmaton results for the full sample In ths secton, we present estmates usng the full sample. Estmaton results n Table 3 are obtaned from both the threshold Tobt method as well as the OLS method. 17 Whle the results of the two methods are generally consstent, the followng dscussons wll focus on those from maxmum lkelhood estmaton of the Tobt model. The frst two columns gve estmates excludng CHIN, the measure for ethnc Chnese networks represented by the product of the numbers of ethnc Chnese of the country pars, as a benchmark. The OLS results suggest that the model explans close to 40 percent of the total varance n FDI. The Tobt model produced sgnfcant estmates for the basc varables wth expected sgns. To explan the estmates n a more conventonal way, we wrte the equaton n terms of GNPs and per capta GNPs as follows. ln(60 + FDI ) = max[ ln GNP ln PGNP 1.01ln PGNP GNP 0.65ln DIST + AX, ln60] 17 When OLS s used to obtan estmates, we defne the dependent varable as ln(fdi+1) to retan observatons wth zero amount of FDI. 18

19 where X represents the other varables n the model. Blateral FDI responds postvely to the GNPs of both source and the host countres and the per capta GNP of the source country, and negatvely to per capta GNP of the host country and the dstance between the two. The hgher a source country s GNP and per capta GNP, the more ts frms wll enoy specfc advantages and benefts from nvestng abroad. For the host countres, the hgher the host countres GNPs and the lower the per capta GNPs, the larger the potental market and the lower the average labor cost. These suggest that cross-border nvestment s motvated by both large markets and lower labor costs. The results also suggest that dstance s a sgnfcant deterrence to FDI between two countres and ts magntude (-0.65), s compatble to that obtaned for trade n dfferentated goods. 18 Before addng measures on ethnc Chnese networks nto the model, we brefly examne the estmates for the other varables of nterests. The members of the European Communty nvest sgnfcantly more wth each other than wth other countres, but ths s not the case for the members of the European Free Trade Assocaton. Furthermore, former colonal tes and a common natve language are also mportant n promotng blateral FDI between countres. The level of a country s tarffs does not have a sgnfcant mpact on ts nward FDI, and tarff umpng was therefore not found to be an mportant motvaton for FDI n our full sample. On the other hand, the rato of a country s total trade to ts GDP s postvely assocated wth ts FDI. We cannot conclude that as evdence of complementarty between trade and FDI. It s hghly plausble that a country pursung an 19

20 open polcy would attract foregn nvestment as well as havng a hgh rato of trade to GDP. In addton, there s no evdence that FDI s drven by the host country s recent GDP growth. On the contrary, the coeffcent on host country GDP growth s negatve and sgnfcant. Ths result mght be due to varous factors. For example, GDP growth rates for some less-developed countres have been qute hgh n recent years, as they started from very low bases. Snce they have opened ther economy to foregn nvestors only for a short perod, the level of accumulated FDI s stll rather low (ths s the case, for example, n Vetnam, Kenya, and Pakstan). On the other hand, ndustral countres whch have accumulated the longest and largest FDI may have suffered a serous slowdown n economc growth n recent years. In addton, the effect of fast growth, ndcatng a large potental market, mght have partally been captured by a country s total GNP. Fnally, we notce that a country remote from the rest of the world seems to be more attractve for FDI. It mght be that the cost of servng a remote market through trade s relatvely hgh and thus drect nvestment s a better alternatve. On the other hand, remoteness from the maor global markets does not seem to be mportant n drvng outward FDI. In addton, there s no sgn that neghborng countres nvest more wth each other. The coeffcent s postvely but statstcally nsgnfcant. Presentatons of estmaton results n the followng paragraphs and n the followng sectons wll focus on the mpact of ethnc Chnese networks. Dscussons on the estmates of the other varables wll be provded only where dfferent estmates are obtaned and comparsons are needed. The thrd and the fourth columns present estmaton results, ncludng a measure on ethnc Chnese networkng, CHIN. It s shown that the ncluson mproves the model 18 In equatons where the dependent varable s blateral annual trade (Rauch and Trndade 2002), the coeffcent on dstance for dfferentated goods range between 0.68 and

21 overall ftness sgnfcantly. The coeffcent on CHIN s postve (0.19 for the Tobt equaton) and sgnfcant, consstent wth the hypothess that ethnc Chnese networks, as represented by the total number of potental nternatonal connectons between two countres, sgnfcantly ncrease blateral FDI. Because of the structure of the threshold Tobt specfcaton, the coeffcents cannot be readly nterpreted as percentage change of FDI n response to a percentage change n the number of Chnese n the two countres. As the estmated threshold, A, s postve and sgnfcant, the presence or the ncrease of ethnc Chnese could mean to ncrease blateral FDI for zero to postve. In that case, the margnal mpact s nfnte. When there exsts postve FDI, the coeffcent s the lower bound for the percentage change of FDI as a result of a 1% ncrease n the product of the numbers of ethnc Chnese n the two countres. In other words, when postve FDI exsts between two countres, a 1% ncrease n the ethnc Chnese populaton n both countres wll correspond to an ncrease n total blateral FDI by at least 0.38% 19. As noted earler, the maorty of overseas Chnese lve n Southeast Asa, and they play a unque and mportant role n the regon s economy. In addton, ethnc Chnese busnesses n the regon are known for ther establshed and actve networkng actvtes across natonal borders. To dentfy the possble dfferent effects of ethnc Chnese networks nvolvng Southeast Asan economes, we dvde country pars nto three groups. In the frst group, both the source and the host country are n Southeast Asa. In the second group, ether the source or the host country s n Southeast Asa. In the thrd group, nether 19 Snce ( ) 2 s roughly FDI from country to country wll ncrease by about by 0.38% as a result of a 1% ncrease of the number of Chnese n both the source and the host country. Smlarly, FDI from country to country wll also ncrease by about 0.38%. 21

22 s n Southeast Asa. Separate estmates on CHIN are obtaned for the three groups and the new estmates are presented n columns 5 and 6 of Table 3. The results show that the new estmates mprove the model sgnfcantly and, ndeed, the effect of ethnc Chnese networks dffers across groups. The hghest coeffcent for CHIN s 0.26 for country pars outsde Southeast Asa. Ths mght suggest that there s decreasng margnal effect of ethnc Chnese networkng on blateral FDI 20. On the other hand, we fnd that the coeffcent for country pars where both countres are n Southeast Asa (0.22) s hgher than where only one of the par s n Southeast Asa (0.16). Ths mght suggest that, ndeed, extensve and actve networks among ethnc Chnese busnesses n Southeast Asa have played key roles n drvng cross-border nvestment n the regon. The above survey suggests that ethnc Chnese networks, approxmated by the product of the numbers of ethnc Chnese n the two countres, are mportant n promotng blateral FDI between all country pars ncluded n ths study. In addton, evdence suggests that the margnal effect of ethnc Chnese networks s hgher for country pars outsde Southeast Asan countres. A 1% ncrease n the total number of ethnc Chnese n each of the two countres corresponds to an ncrease of about 0.52% n total blateral FDI. For country pars nvolvng Southeast Asan countres, the correspondng change n blateral FDI s 0.44% where both countres are n Southeast Asa and 0.30% where only one of the par s n Southeast Asa. 20 ln CHIN s when both country and country are n Southeast Asa, when ether or s n Southeast Asa, and 9.38 when nether nor s n Southeast Asa. 22

23 B. Industral vs. developng countres & ethnc Chnese networks Our dscusson earler suggests that FDI orgnatng from developng economes may demonstrate dfferent features than that from ndustral countres. In ths secton we dvde the full sample nto two sub-groups accordng to the source countres of blateral FDI 21 and estmate the emprcal equaton separately. In the left panel of Table 4, the dependent varable s blateral FDI orgnatng from ndustral countres; n the rght panel, the dependent varable s FDI orgnatng from developng economes. In general, the results from the two panels are qualtatvely the same, 22 whle OLS estmaton ndcates that the gravty model specfcaton accounts for a larger porton of total varance for FDI orgnatng from ndustral countres than from developng countres. The adusted R- square s more than 40% for the left panel, and about 22% for the rght panel. On the other hand, the results suggest that the percentage change n blateral FDI n response to a percentage change n the basc factors dffers n magntude between the left and the rght panels. Ths becomes clear f we rewrte the equatons n the followng format based on the second column two panels n Table 4. For FDI orgnatng from ndustral countres, we have the followng. ln(152 + FDI ) = max[ ln GNP ln PGNP 0.65 ln PGNP GNP 0.70 ln DIST + AX, ln152] Smlarly, for FDI from developng economes, the equaton s as follows. ln(33 + FDI ) = max[ ln GNP ln PGNP 1.37 ln PGNP GNP 0.48 ln DIST + AX, ln33] 21 Industral countres nclude Australa, Canada, Japan, New Zealand, the Unted States, and all members of the European Communty and European Free Trade Assocaton. 22 The estmates for the two panels have the same sgns when they are wrtten n terms of GNPs and per capta GNPs of the source and the host countres. 23

24 The results show that FDI from ndustral countres s more senstve to source country characterstcs, whle FDI from developng countres s more senstve to host country characterstcs. One possble explanaton s that, as multnatonals from developng countres possess relatvely less frm specfc assets, cost advantage n a foregn locaton s a much stronger motvaton for relocaton of producton. In addton, dstance s a more sgnfcant deterrent to FDI from ndustral countres. A shared natve language s mportant for nvestors n ndustral countres, but s almost rrelevant for nvestors n developng countres. Columns 3 through 6 gve model estmates whle measures on ethnc Chnese networkng are ncluded. In both panels, the ncluson mproves the model sgnfcantly. In general, seen from columns 3 and 4, the mpact of ethnc Chnese networks s postve and sgnfcant. The magntude of the estmates CHIN s larger for FDI orgnatng from ndustral countres (0.28) than that for FDI from developng countres (0.15). The results ndcate that ethnc Chnese networkng s sgnfcant n promotng blateral FDI from both ndustral countres and developng countres. The mportance, on the margn, seems to be stronger for nvestment orgnatng from ndustral countres. In columns 5 and 6 of both panels, separate estmates on CHIN are obtaned for three groups of country pars accordng to the nvolvement of Southeast Asan economes. For nvestors n ndustral countres (left panel), ethnc Chnese networks, agan on the margn, are less mportant for nvestment to Southeast Asa (0.22) than to other countres (0.36), such as those n Europe and Amerca. Ths s consstent wth the decreasng margnal effect of ethnc networks between countres. For nvestors n developng countres (rght panel), ethnc Chnese networks are most mportant between Southeast 24

25 Asan economes. The coeffcent on CHIN s 0.22 and sgnfcant. Investment from Southeast Asa n other regons also responds postvely to changes n CHIN, but the magntude s much smaller (0.10). Fnally, ethnc Chnese networks do not seem to sgnfcantly affect nvestors n developng countres outsde Southeast Asa when they nvest n regons outsde Southeast Asa. The coeffcent s postve but statstcally nsgnfcant. Ths s n contrast to the decreasng margnal effect of ethnc Chnese networks. That s to say, for nvestors n developng countres, ethnc networks are effectve only when ntensve networkng actvtes are present. Our basc gravty model specfcaton has provded consstent results for the two sub-samples whle the overall ftness of the model s better when FDI from ndustral countres s used n the estmaton. More mportantly, ethnc Chnese networkng s found to be mportant n promotng drect nvestment except when FDI s between two countres outsde Southeast Asa and, at the same tme, the FDI source s a developng country. An example would be nvestment from Mexco to Brazl or to France. C. Bureaucratc qualty & ethnc Chnese networks Our dscussons suggest that there are two mechansms through whch ethnc Chnese networks promote blateral FDI: communty enforcement of sanctons and assstance n overcomng nformatonal barrers. Assumng the frst mechansm s mportant manly for nvestment destned to countres wth weak nsttutons, we may be able to evaluate the two effects by dvdng the blateral FDI nto two groups, dependng on the level of bureaucratc qualty n the host countres. In the left panel of Table 5, the dependent varable s drect nvestment to countres where bureaucratc qualty s relatvely 25

26 hgh 23. In the rght panel, the dependent varable s FDI destned to countres where the bureaucratc qualty s relatvely low. If we beleve that economc development s postvely correlated wth a country s nsttutonal development, we could also thnk of the frst as FDI to countres wth a relatvely hgher level of economc development. In general, the models explan more than 40 percent of total varance n total blateral FDI between countres. To compare the estmates on the basc varables, we present the equatons n terms of the countres GNP and per capta GNPs (column 2). For FDI to countres wth hgh bureaucratc qualty we have the followng. ln(93 + FDI ) = max[ ln GNP ln PGNP GNP 1.72 ln PGNP 0.48 ln DIST + AX, ln93] For FDI to countres wth low bureaucratc qualty, we have the followng. ln(26 + FDI ) = max[ ln GNP ln PGNP 0.41ln PGNP GNP 1.08 ln DIST + AX, ln26] In both equatons, the coeffcents for the basc varables, as well as for most of the addtonal varables, have same sgns but dffer n magntude. There are nevertheless some sgnfcant dfferences. In the left panel, where FDI destned to countres wth hgh bureaucratc qualty s used, the coeffcents on the measures of formal colonal tes and of common brth language are both postve and sgnfcant. In the rght panel, where FDI destned to countres wth low bureaucratc qualty s used, nether of the two coeffcents s sgnfcant. Perhaps the most mportant contrast between the two panels s the coeffcent for the host country s average tarff rate. The estmate s negatve n the left panel but postve n the rght panel, both statstcally sgnfcant. It suggests that tarff umpng 23 The score for a country s bureaucratc qualty ranges from 0 to 6. The mean value s about 3.6. FDI to two countres are excluded from the analyss, as the score of bureaucratc qualty for the two countres s

27 mght be the motvaton for some drect nvestments, especally nvestments n countres wth low levels of economc and nsttutonal development. The results n columns 3 and 4 of both panels are obtaned when the measure on ethnc Chnese networks s ncluded. The ncluson mproves the overall model sgnfcantly. The coeffcent on CHIN s 0.31 n the left panel and 0.07 n the rght panel, both sgnfcant. The results show that ethnc Chnese networks are mportant n facltatng blateral FDI between countres, regardless of the nsttutonal development status of the host countres. In addton to communty enforcement of sanctons, whch s mportant for FDI to countres wth weak nsttutons, ethnc Chnese also promote FDI through provdng crucal nformaton. The latter mght be a more mportant mechansm. Fnally, we estmate the effect of ethnc Chnese networks for dfferent country pars dependng on whether the source and/or host countres are n Southeast Asa (columns 5 and 6). The mprovement on the model s sgnfcant (margnally for the rght panel). In the left panel, all three estmates for CHIN are postve and hghly sgnfcant. The magntude s the hghest for country pars where nether s n Southeast Asa and the lowest when only one of the par s n the regon. In the rght panel, all three estmates are postve, but the estmate where ether the source or the host s n Southeast Asa s statstcally nsgnfcant. The results are consstent wth earler fndngs that ethnc Chnese networks seem to be most effectve n promotng blateral FDI between countres outsde Southeast Asa. Ethnc networks are also very mportant for FDI between Southeast Asan economes. 27

28 V. Concludng Remarks Usng a standard gravty model, ths paper examnes the mpact of ethnc Chnese networks n promotng blateral FDI between countres. We conclude that ethnc Chnese networks play a crucal role n facltatng drect nvestment not only between Southeast Asan economes but also between economes elsewhere n the world. By usng data on FDI from the Unted Natons, we are able to nvestgate the mportance of ethnc networkng on drect nvestment orgnatng from developng countres separately from those from ndustral countres. Although the gravty model s not as effectve n predctng FDI from developng countres than from ndustral countres, ethnc Chnese networks are found sgnfcant n promotng blateral FDI n both cases. By estmatng separate models on FDI destned to countres wth weak and strong nsttutons respectvely, the study also fnds evdence that both mechansms are mportant for ethnc Chnese networks. For nvestment to countres wth weak nsttutons, ethnc networks provde communty enforcement of sanctons to deter cheatng actvtes and to promote nvestment. Ths s partcularly effectve for nvestment between Southeast Asa economes where extensve ethnc Chnese networks have long been actve. For countres wth good nsttutons, on the other hand, the more mportant mechansm of ethnc networks s to help nvestors overcome nformatonal barrers n ther nvestment decsons. Whle t s dffcult to evaluate the relevant mportance of the two mechansms, the estmates on CHIN are much larger for FDI to countres wth a hgh level of nsttutonal development, suggestng that nformaton mght be a more mportant beneft n facltatng FDI. 28

29 Our emprcal results have also generated some nterestng fndngs on the determnants of FDI. In general, we fnd that nvestment from developng countres s drven by a large market sze and low labor costs n the host countres, ust as n the case of ndustral countres. A large economy and ncreasng labor costs n source countres encourages more drect nvestment abroad. In addton, membershp of the EC, former colonal tes and a shared natve language are also mportant nfluences on FDI, especally for nvestors n ndustral countres. We also fnd that nvestment and trade seem to complement each other, as FDI s postvely related to the host countres trade ntensty. On the other hand, there s also evdence that tarff umpng s an mportant motvaton for nvestment. FDI to countres wth weak nsttutons responds postvely to host countres average tarff rate. What can we learn from ths study? We fnd that ethnc Chnese networks play a sgnfcant role n promotng blateral FDI between countres n a rather broader sense, mplyng that the effectveness should not be lmted to ethnc Chnese. Two questons reman for future studes. Frst, can we fnd evdence of the effect of networkng actvtes of other ethnc groups n promotng trade and nvestment? Second, wll the effectveness of ethnc networkng decrease wth the development of new technologes that make nformaton exchange faster, easer, and less costly? 29

30 Appendx A: Data source and defnton for foregn drect nvestment Data on each country s blateral foregn drect nvestment stocks were obtaned from Table 9, Geographcal locaton of FDI stocks, n the World Investment Drectory. Sx volumes of the Drectory have been publshed snce Volume Two ncludes all developed countres. Each of the other volumes ncludes developng countres n a regon, such as Asa and the Pacfc, the Amercas, Central and East Europe, and Afrca and West Asa. There are two man defntons of FDI. One s contaned n the Balance of Payments Manual (Washngton DC, Internatonal Monetary Fund, 1977) and the other n the Detaled Benchmark Defnton of Foregn Drect Investment (Pars, Organzaton for Economc Cooperaton and Development, 1983). Both are used n the Drectory. Accordng to the Balance of Payments Manual, FDI refers to nvestment made to acqure lastng nterest n enterprses operatng outsde the economy of the nvestor. Further, n cases of FDI the nvestor s purpose s to gan an effectve voce n the management of the enterprses. Some degree of equty ownershp s almost always consdered to be assocated wth an effectve voce n the management of an enterprse; however, IMF does not specfy an exact percentage of equty ownershp that qualfes an nvestor as a foregn drect nvestor. 30