American Political Science Review Vol.104,No.3 to control-as completely as possible-for other mea- Sample and Methods sures of culture and familiarity.To that end,we include a number of measures that capture cultural similari- To examine the link between migrant networks and ties between the source and destination countries.The bilateral portfolio investment,we use data from the first-a measure of common legal origin-is more in- International Monetary Fund's (IMF's)Coordinated stitutional than cultural,but it captures the ability of Portfolio Investment Survey(CPIS).The CPIS collects investors from country s to invest in country d with information on the stock of cross-border investments minimal transaction costs because they will already in equities and in short-and long-term bonds broken be familiar with the rules and regulations.We expect down by issuer's country of residence.19 Due to data that country pairs with common legal origins will ex- constraints.we are able to use data on the investment perience higher levels of cross-border investment than portfolio of 56 source (reporting)countries and 154 those pairs with dissimilar legal origins. destination countries.20 The list of source and destina- Our second control for cultural similarity is a mea- tion countries is contained in Appendix C. sure of cultural proximity that is created through the Our data on FDI come from the OECD's Interna- creation of a dummy variable measuring whether the tional Direct Investment.This source is limited in that two countries have a common dominant religion.Com it only provides data for outflows from OECD coun- mon religion proxies for similar beliefs,values,and ex- tries.Therefore,when we look at bilateral FDI,our pectations regarding the existence of social norms and sample is restricted to one of 28 source countries and the internally imposed constraints that are important 158 destination countries. for a business partnership across borders. Our key independent variable-that of migrant The third cultural control is grounded in cultural networks-measures the stock (or total number)of mi- economics and operationalized as a measure of ge- grants from country d residing in country s.These data netic distance between countries.Based on the work come from a World Bank project on South-South mi- of Cavalli-Sforza,Menozzi,and Piazza (1994),schol- gration and remittances.They are based on data from ars have developed measures of genetic distances be- national statistical bureaus (censuses and population tween indigenous populations based on genetic or registers)and secondary sources(the OECD,the Inter- DNA polymorphism.18 This measure of genetic dis- national Labour Organization,and the UN).A 162 x tance has been used to proxy for culture in studies of 162 matrix of the migrant stock in country s from coun- international trade and FDI (Giuliano,Spilimbergo. try d classified according the migrant's country of birth and Tonon 2006:Guiso,Sapienza,and Zingales 2005). is constructed from these national sources (Ratha and economic development(Spolaore and Wacziarg 2008). Shaw 2007).Although some of the underlying data and state formation in Europe (Desmet et al.2007). are from the late 1990s,the majority correspond to Desmet et al.provide evidence that European coun- migrant stock for 2000 or 2001.Consequently,we are tries that are genetically alike have populations that restricted to working with cross-sectional and not time- provide similar answers to World Values Survey ques- series data. tions about cultural,religious,and moral issues. We estimate Equation (1)using ordinary least Finally,we include a more direct measure of cul- squares(OLS)and control for source-and destination tural similarity.Studies in international business find country-specific variables through the use of a double that greater cultural distance between countries is as- set of fixed effects.Inferences based on OLS standard sociated with larger transactions costs,higher uncer- errors may,however.be underestimated.This bias may tainty about business practices,and overall greater un be attributable to two related causes.First,investment ease regarding the prospects for doing business (e.g. by source countries may cluster geographically;conse- Habib and Zurawicki 2002;Kogut and Singh 1988; quently,we may need standard errors that are clustered Siegel,Licht,and Schwartz 2008).Some recent stud- by s.Second,some destination countries,for a multi- ies of international trade find that culturally similar tude of reasons,receive more investment than other countries engage in larger levels of transactions (e.g. Guiso,Sapienza,and Zingales 2005;Siegel,Licht,and Schwartz 2008;White and Tadesse 2008).Following 19 Lane and Milesi-Ferretti (2004)and Eichengreen and Lueng. this lead.we use a measure of cultural difference or naruemitchai(2006)point out some advantages and disadvantages of distance based on questions from the World Values the CPIS data.In designing the survey,the IMF attempted to ensure Survey.Unfortunately,these surveys are only given in comparability across countries;to that end,the surveys are structured to prevent double counting.With that said,the CPIS does not report 95 countries,so their use limits the size of our sample; the domestic holdings of investors,which makes testing theories of consequently,we include these measures as a robust- portfolio allocation and home bias difficult with these data,and it ness check is possible that there is some underreporting.Most significantly,for our purposes,the CPIS does not have data on the foreign holdings of a few large origin countries,including China and Saudi Arabia (although it does have these countries as destinations). 2 As in Rose and Spiegel (2008),we use the average of portfolio investment for 2002,2003,and 2004 because response rates for these 18 The details involved in the derivation of these measures in and of years differ broadly by country.Pooling these years allows us to themselves constitute a paper.The interested reader is directed to almost double the sample size.The correlation between portfolio Spolaore and Wacziarg(2008)for a discussion and application.We investment for 2002 and the average from 2002 to 2004 is 0.91.For are grateful to Spolaore and Wacziarg for generously sharing their the purpose of comparability,we construct the dependent variable data. for FDI in a similar manner. 589American Political Science Review Vol. 104, No. 3 to control—as completely as possible—for other mea￾sures of culture and familiarity. To that end, we include a number of measures that capture cultural similari￾ties between the source and destination countries. The first—a measure of common legal origin—is more in￾stitutional than cultural, but it captures the ability of investors from country s to invest in country d with minimal transaction costs because they will already be familiar with the rules and regulations. We expect that country pairs with common legal origins will ex￾perience higher levels of cross-border investment than those pairs with dissimilar legal origins. Our second control for cultural similarity is a mea￾sure of cultural proximity that is created through the creation of a dummy variable measuring whether the two countries have a common dominant religion. Com￾mon religion proxies for similar beliefs, values, and ex￾pectations regarding the existence of social norms and the internally imposed constraints that are important for a business partnership across borders. The third cultural control is grounded in cultural economics and operationalized as a measure of ge￾netic distance between countries. Based on the work of Cavalli-Sforza, Menozzi, and Piazza (1994), schol￾ars have developed measures of genetic distances be￾tween indigenous populations based on genetic or DNA polymorphism.18 This measure of genetic dis￾tance has been used to proxy for culture in studies of international trade and FDI (Giuliano, Spilimbergo, and Tonon 2006; Guiso, Sapienza, and Zingales 2005), economic development (Spolaore and Wacziarg 2008), and state formation in Europe (Desmet et al. 2007). Desmet et al. provide evidence that European coun￾tries that are genetically alike have populations that provide similar answers to World Values Survey ques￾tions about cultural, religious, and moral issues. Finally, we include a more direct measure of cul￾tural similarity. Studies in international business find that greater cultural distance between countries is as￾sociated with larger transactions costs, higher uncer￾tainty about business practices, and overall greater un￾ease regarding the prospects for doing business (e.g., Habib and Zurawicki 2002; Kogut and Singh 1988; Siegel, Licht, and Schwartz 2008). Some recent stud￾ies of international trade find that culturally similar countries engage in larger levels of transactions (e.g., Guiso, Sapienza, and Zingales 2005; Siegel, Licht, and Schwartz 2008; White and Tadesse 2008). Following this lead, we use a measure of cultural difference or distance based on questions from the World Values Survey. Unfortunately, these surveys are only given in 95 countries, so their use limits the size of our sample; consequently, we include these measures as a robust￾ness check. 18 The details involved in the derivation of these measures in and of themselves constitute a paper. The interested reader is directed to Spolaore and Wacziarg (2008) for a discussion and application. We are grateful to Spolaore and Wacziarg for generously sharing their data. Sample and Methods To examine the link between migrant networks and bilateral portfolio investment, we use data from the International Monetary Fund’s (IMF’s) Coordinated Portfolio Investment Survey (CPIS). The CPIS collects information on the stock of cross-border investments in equities and in short- and long-term bonds broken down by issuer’s country of residence.19 Due to data constraints, we are able to use data on the investment portfolio of 56 source (reporting) countries and 154 destination countries.20 The list of source and destina￾tion countries is contained in Appendix C. Our data on FDI come from the OECD’s Interna￾tional Direct Investment. This source is limited in that it only provides data for outflows from OECD coun￾tries. Therefore, when we look at bilateral FDI, our sample is restricted to one of 28 source countries and 158 destination countries. Our key independent variable—that of migrant networks—measures the stock (or total number) of mi￾grants from country d residing in country s. These data come from a World Bank project on South–South mi￾gration and remittances. They are based on data from national statistical bureaus (censuses and population registers) and secondary sources (the OECD, the Inter￾national Labour Organization, and the UN). A 162 × 162 matrix of the migrant stock in country s from coun￾try d classified according the migrant’s country of birth is constructed from these national sources (Ratha and Shaw 2007). Although some of the underlying data are from the late 1990s, the majority correspond to migrant stock for 2000 or 2001. Consequently, we are restricted to working with cross-sectional and not time￾series data. We estimate Equation (1) using ordinary least squares (OLS) and control for source- and destination country–specific variables through the use of a double set of fixed effects. Inferences based on OLS standard errors may, however, be underestimated. This bias may be attributable to two related causes. First, investment by source countries may cluster geographically; conse￾quently, we may need standard errors that are clustered by s. Second, some destination countries, for a multi￾tude of reasons, receive more investment than other 19 Lane and Milesi-Ferretti (2004) and Eichengreen and Lueng￾naruemitchai (2006) point out some advantages and disadvantages of the CPIS data. In designing the survey, the IMF attempted to ensure comparability across countries; to that end, the surveys are structured to prevent double counting. With that said, the CPIS does not report the domestic holdings of investors, which makes testing theories of portfolio allocation and home bias difficult with these data, and it is possible that there is some underreporting. Most significantly, for our purposes, the CPIS does not have data on the foreign holdings of a few large origin countries, including China and Saudi Arabia (although it does have these countries as destinations). 20 As in Rose and Spiegel (2008), we use the average of portfolio investment for 2002, 2003, and 2004 because response rates for these years differ broadly by country. Pooling these years allows us to almost double the sample size. The correlation between portfolio investment for 2002 and the average from 2002 to 2004 is 0.91. For the purpose of comparability, we construct the dependent variable for FDI in a similar manner. 589