Familiarity Breeds Investment August 2010 facilitating investment and in further integrating their receive capital tend to have better institutions,more countries into the global economy.Gamlen (2008) stable economic policies,and better governance.14 notes that even developed states such as New Zealand. All empirical models are vulnerable to problems of Ireland,and Israel have well-developed diaspora en- omitted variable bias.We choose a very conservative gagement strategies designed to encourage active eco- strategy and estimate a cross-sectional model of bilat- nomic behavior on the part of their external citizens eral investment that contains fixed effects for both the In a response to a question from a member of their source and destination countries.Although this estima- parliament about how Scotland intends to engage their tion strategy sacrifices some richness in that we cannot diaspora residing in Canada,Scottish Executive Min- explore variation in host and homeland domestic insti- ister for Parliament declared,"The Scottish Executive tutions and policies,it allows us to concentrate on bi- intends to engage with and mobilize the Scottish dias- lateral characteristics that influence dyadic investment. pora to further Scotland's interests for the long-term Concretely,we write our model as benefit of our economy and society.We aim to encour- age the diaspora's active participation and engagement log0y)sd=δs+δd+φlog(I)+βXd+csd, (1) in promoting Scotland as a great country to visit,live, learn,work,do business and invest."13 Because they increase familiarity and decrease in- where ysd is the level of either portfolio or FDI from formation asymmetries,we hypothesize that larger mi- a source country (s)into a destination country (d).15 grant networks,all other things being equal,will exert Because we are working with a cross-section of country a positive influence on cross-border investment.The dyads,we control for unmeasured source and destina- effect of migrant networks should increase when the tion country characteristics through the inclusion of migrants themselves are the entrepreneurs,but this two sets of dummy variables:δ，andδa.Our variable increase may also be due to their ability to provide in- of interest is the log of the migrant stock (Ids)-the formation about opportunities to the investment com- population of migrants-from the destination country munity.Following Rauch and Trindade (2002),we also residing in the source country. hypothesize that migrant networks will be more im- The vector (Xsd)includes variables other than mi- portant for investment in heterogeneous(as compared grant stock that potentially influence cross-border in- with homogeneous)assets.This is because informa- vestment.Drawing on gravity-type models of FDI and tion costs-both asymmetries and transactions costs- portfolio investment,16 we control for the dyad's mar- associated with heterogeneous assets are substantially ket size,the bilateral distance between countries,the larger than those associated with homogeneous assets. existence of a common border,and a shared common When it comes to cross-border investment,we argue language.17 Market size is measured as the log of the that FDI is far more heterogeneous than portfolio in- product of the two country's gross domestic products vestment.Whereas portfolio investors choose debt or (GDPs).Given that distance is an imperfect measure equity stakes that are offered by an issuing agency of information costs,following Portes and Rey(2005). on an organized market,foreign direct investors can we include the log of bilateral telephone traffic take innumerable different ownership stakes across a Trade-in financial assets may also be influenced by countless number of commodity classes.We hypothe- shared policy variables.As in Lane and Milesi-Ferretti size,therefore,that migrant networks will have a larger (2004),we include variables capturing whether the two substantive effect on FDI than on portfolio investment. countries share a common exchange rate peg,have a It may be the case that migrant networks do not dual taxation treaty,or are members of a preferential matter at all and that they just proxy for greater cul- trade agreement.Given the importance of portfolio tural or informational similarities among countries- diversification in ICAPMs,we proxy for common eco- the sorts of variables identified in empirical studies of nomic shocks by including the (lagged)correlation of ICAPMs.To decrease the risk of incorrect inferences, the two country's growth rates. we go to great lengths to control for a variety of ways As discussed previously,it is difficult to differentiate that countries are connected with one another. between investment due to cultural affinity,market fa- miliarity,or information asymmetry.Our approach is EMPIRICS 14 See Alfaro.Kelemli-Ozcan,and Volosovych (2006).Buthe and Model and Variables Milner (2008).and Jensen (2003)for a discussion of destination country factors that are correlated with capital inflows. In addition to migrant networks,there are scores of is Source and destination countries are listed in Appendix A while factors that conceivably effect investment between two variable sources and definitions are contained in Appendix B. 16 Studies of FDI employing a gravity model include Wei (2000)and countries.In the source country,capital outflows can Loungani,Mody,and Razin (2002).Portes,Rey,and Oh(2001),Lane be influenced by high tax rates,the lack of protection and Milesi-Ferretti(2004),Portes and Rey (2005),Lane (2005),and for private property,high savings rates,etc.A similar Eichengreen and Luengnaruemitchai(2006)use a gravity model to list can be made for recipient countries:countries that examine bilateral investment in equities and bonds. 17 Some gravity models also include a variable indicating whether the two countries were ever in a colonial relationship.When included in our models,this variable was never statistically significant.We omit 13 Quoted from www.martinfrost.ws/htmlfiles/gazette/scot_diaspora. it from our specification because we also include a measure of shared html. legal origin as it is highly correlated with colonial status. 588Familiarity Breeds Investment August 2010 facilitating investment and in further integrating their countries into the global economy. Gamlen (2008) notes that even developed states such as New Zealand, Ireland, and Israel have well-developed diaspora en￾gagement strategies designed to encourage active eco￾nomic behavior on the part of their external citizens. In a response to a question from a member of their parliament about how Scotland intends to engage their diaspora residing in Canada, Scottish Executive Min￾ister for Parliament declared, “The Scottish Executive intends to engage with and mobilize the Scottish dias￾pora to further Scotland’s interests for the long-term benefit of our economy and society. We aim to encour￾age the diaspora’s active participation and engagement in promoting Scotland as a great country to visit, live, learn, work, do business and invest.”13 Because they increase familiarity and decrease in￾formation asymmetries, we hypothesize that larger mi￾grant networks, all other things being equal, will exert a positive influence on cross-border investment. The effect of migrant networks should increase when the migrants themselves are the entrepreneurs, but this increase may also be due to their ability to provide in￾formation about opportunities to the investment com￾munity. Following Rauch and Trindade (2002), we also hypothesize that migrant networks will be more im￾portant for investment in heterogeneous (as compared with homogeneous) assets. This is because informa￾tion costs—both asymmetries and transactions costs— associated with heterogeneous assets are substantially larger than those associated with homogeneous assets. When it comes to cross-border investment, we argue that FDI is far more heterogeneous than portfolio in￾vestment. Whereas portfolio investors choose debt or equity stakes that are offered by an issuing agency on an organized market, foreign direct investors can take innumerable different ownership stakes across a countless number of commodity classes. We hypothe￾size, therefore, that migrant networks will have a larger substantive effect on FDI than on portfolio investment. It may be the case that migrant networks do not matter at all and that they just proxy for greater cul￾tural or informational similarities among countries— the sorts of variables identified in empirical studies of ICAPMs. To decrease the risk of incorrect inferences, we go to great lengths to control for a variety of ways that countries are connected with one another. EMPIRICS Model and Variables In addition to migrant networks, there are scores of factors that conceivably effect investment between two countries. In the source country, capital outflows can be influenced by high tax rates, the lack of protection for private property, high savings rates, etc. A similar list can be made for recipient countries: countries that 13 Quoted from www.martinfrost.ws/htmlfiles/gazette/scot_diaspora. html. receive capital tend to have better institutions, more stable economic policies, and better governance.14 All empirical models are vulnerable to problems of omitted variable bias. We choose a very conservative strategy and estimate a cross-sectional model of bilat￾eral investment that contains fixed effects for both the source and destination countries. Although this estima￾tion strategy sacrifices some richness in that we cannot explore variation in host and homeland domestic insti￾tutions and policies, it allows us to concentrate on bi￾lateral characteristics that influence dyadic investment. Concretely, we write our model as log(y)sd = δs + δd + φ log(Ids) + βXsd + εsd, (1) where ysd is the level of either portfolio or FDI from a source country (s) into a destination country (d).15 Because we are working with a cross-section of country dyads, we control for unmeasured source and destina￾tion country characteristics through the inclusion of two sets of dummy variables: δs and δd. Our variable of interest is the log of the migrant stock (Ids)—the population of migrants—from the destination country residing in the source country. The vector (Xsd) includes variables other than mi￾grant stock that potentially influence cross-border in￾vestment. Drawing on gravity-type models of FDI and portfolio investment,16 we control for the dyad’s mar￾ket size, the bilateral distance between countries, the existence of a common border, and a shared common language.17 Market size is measured as the log of the product of the two country’s gross domestic products (GDPs). Given that distance is an imperfect measure of information costs, following Portes and Rey (2005), we include the log of bilateral telephone traffic. Trade-in financial assets may also be influenced by shared policy variables. As in Lane and Milesi-Ferretti (2004), we include variables capturing whether the two countries share a common exchange rate peg, have a dual taxation treaty, or are members of a preferential trade agreement. Given the importance of portfolio diversification in ICAPMs, we proxy for common eco￾nomic shocks by including the (lagged) correlation of the two country’s growth rates. As discussed previously, it is difficult to differentiate between investment due to cultural affinity, market fa￾miliarity, or information asymmetry. Our approach is 14 See Alfaro, Kelemli-Ozcan, and Volosovych (2006), Buthe and ¨ Milner (2008), and Jensen (2003) for a discussion of destination country factors that are correlated with capital inflows. 15 Source and destination countries are listed in Appendix A while variable sources and definitions are contained in Appendix B. 16 Studies of FDI employing a gravity model include Wei (2000) and Loungani, Mody, and Razin (2002). Portes, Rey, and Oh (2001), Lane and Milesi-Ferretti (2004), Portes and Rey (2005), Lane (2005), and Eichengreen and Luengnaruemitchai (2006) use a gravity model to examine bilateral investment in equities and bonds. 17 Some gravity models also include a variable indicating whether the two countries were ever in a colonial relationship. When included in our models, this variable was never statistically significant. We omit it from our specification because we also include a measure of shared legal origin as it is highly correlated with colonial status. 588