Nations of entrepreneurs: A social capital perspective

Journal of Business Venturing 25 (2010) 315–330

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Journal of Business Venturing

Nations of entrepreneurs: A social capital perspective☆ Seok-Woo Kwon a,⁎, Pia Arenius b,1 a b

Assistant Professor of Entrepreneurship, A. Gary Anderson Graduate School of Management, University of California at Riverside, Riverside, CA 92521, United States Turku School of Economics, Pori Unit, Finland

a r t i c l e

i n f o

Article history: Received 6 August 2008 Received in revised form 7 October 2008 Accepted 7 October 2008 Keywords: Social capital Entrepreneurial opportunity perception Weak tie investment Cross-national study

a b s t r a c t This research examined the effects of social capital on entrepreneurial opportunity perception and weak tie investment using individual-level data from the Global Entrepreneurship Monitor linked with national-level data on social capital. Consistent with a social capital perspective, this study found that a resident of a country with higher generalized trust and breadth of formal organizational memberships was more likely to perceive entrepreneurial opportunities. A resident of a country with higher generalized trust was also more likely to invest in an entrepreneur with whom he or she had a weak personal tie than was a resident of a country with lesser generalized trust. Published by Elsevier Inc.

1. Executive summary Current research on entrepreneurship clearly documents the importance of social capital, stressing the ways in which individuals take advantage of their own social affiliations and network strategies in pursuit of their entrepreneurial goals (for a review, see Hoang and Antoncic, 2003). While this focus on personal networks of individual entrepreneurs has yielded valuable insights for understanding entrepreneurship at the individual level, we know relatively little about whether social capital at the societal level contributes to entrepreneurial activities in different countries. To address this gap, we pose these research questions: Do features of social capital at the country level explain cross-national variation in (1) entrepreneurial opportunity perception and (2) weak tie investment (i.e., investment in an entrepreneur with a weak personal tie to the investor)? We define national social capital as a resource reflecting the character of social relations within the nation, expressed in residents' levels of generalized trust and breadth of formal organization memberships (e.g., Knack and Keefer, 1997; La Porta et al., 1997; Paxton, 1999). We explored the influence of national social capital on entrepreneurial activities using data from the Global Entrepreneurship Monitor (GEM) project linked with social capital data from the World Values Survey (WVS) and other country-level data from multiple sources. Multi-level modeling that included country-level control variables (e.g., GDP, ethnic and cultural diversity, and availability of institutional loans) as well as individual-level variables (e.g., demographic and person-specific attributes) was used for this study. Our study found that individual-level attributes influenced opportunity perception and weak tie investment significantly. This suggested that people who perceive entrepreneurial opportunities or invest in a weak tie share common personal attributes that are distinct from those who do not, regardless of their national context. At the same time, though, we also found that the

☆ We thank Scott Hankins, Colleen Heflin, Joe Labianca, Ajay Mehra, and Don Siegel for comments on earlier versions of this article. We also appreciate the criticisms and suggestions of the JBV reviewers and Philip Phan, who helped us refine our arguments and analyses. ⁎ Corresponding author. E-mail addresses: [email protected] (S.-W. Kwon), pia.arenius@tse.fi (P. Arenius). 1 Tel.: +358 50 38 62 780. 0883-9026/$ – see front matter. Published by Elsevier Inc. doi:10.1016/j.jbusvent.2008.10.008

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magnitude of the effects of social capital at the country level was nontrivial: even after controlling for individual- and other country-level attributes, national social capital increased opportunity perception and weak tie investment. The findings have an important implication for theories of entrepreneurship. To date, major theories have focused on the role of individual entrepreneurs in discovering or recognizing opportunities. While this study also found individual-level effects, it extends these individual-level theories by suggesting that the social context in which an entrepreneur is embedded, especially social capital at the country level, is an additional and important contributor to entrepreneurship. 2. Introduction There is a growing literature suggesting that social capital at the national level is positively associated with investment and growth at the country level. Knack and Keefer (1997), for example, show that an increase of one standard deviation in countrylevel trust predicts an increase in economic growth of more than one-half of a standard deviation for a sample of 29 countries. Using a bigger sample of 41 countries, Zak and Knack (2001) show that, controlling for other influences, national growth rises by nearly 1% for each 15 percentage point increase in trust. La Porta et al. (1997) also find that, holding per capita GNP constant, an increase in trust raises large firms' share of the economy for a sample of 40 countries. If social capital influences the economic development of a country significantly, it seems reasonable to expect that social capital would have some influence on the entrepreneurial activities of a country as well: We suggest this because economic activities are also significantly driven by a high level of entrepreneurial activities in a country (Schumpeter, 1942). However, social capital research has not adequately addressed this causal link at the country level—for an early exception to this claim, see Tocqueville and Reeve (1835)—and, instead, tends to focus on a micro perspective at the individual level. Thus, an extensive body of theoretical and empirical research now exists which links personal networks of individuals with opportunity recognition (Arenius and De Clercq, 2005; Davidsson and Honig, 2003), resource acquisition (Aldrich and Zimmer, 1986; Shane and Cable, 2002), the creation of new ventures (Johannisson and Ramirez-Pasillas, 2001), and venture performance (Honig, 1998; Ruef, 2002). However, the question of whether and how social capital at the societal level encourages entrepreneurial activities in a country has been overlooked by entrepreneurship researchers. This is unfortunate since there is growing evidence that social networks of individual entrepreneurs are embedded in the broader societal context (e.g., Dodd and Patra, 2002; Staber and Aldrich, 1995) and that actions and outcomes of individual actors are influenced not just by their dyadic relationships with network contacts but also by social environments at large (Granovetter, 1992). For those reasons, the previous research that focuses only on the dyadic network ties of individuals runs the risk of neglecting contextual factors that can significantly facilitate or constrain individual social capital (Adler and Kwon, 2002). This risk is even greater in international entrepreneurship research, given that researchers have empirically documented a large cross-national variation in social capital at the societal level (e.g., Paxton, 2002; Schofer and Fourcade-Gourinchas, 2001). To address this gap in the extant research on the relationship between entrepreneurship and social capital at the societal level, we pose these research questions: Do features of social capital at the country level explain cross-national variation in (1) entrepreneurial opportunity perception and (2) weak tie investment (i.e., investment in an entrepreneur with a weak personal tie to the investor)? We focus on these entrepreneurial phenomena first, because much of entrepreneurship involves seeking new opportunities and investments (Shane and Venkataraman, 2000), and second, because recognizing such entrepreneurial and investment opportunities is conditioned by the entrepreneur's social context (Jack and Anderson, 2002). While we acknowledge that opportunity perception and weak tie investment are individual-level phenomena, we argue that they are embedded in the societal context and, thus, shaped by its social capital. In the following sections, we formulate hypotheses on the above question and test these hypotheses with unique datasets that permit cross-level modeling. 3. Theoretical framework and hypotheses Our focus here is on social capital as an attribute of a nation. We define national social capital as a resource reflecting the character of social relations within the nation, expressed in residents' levels of generalized trust and breadth of formal organization memberships (e.g., Knack and Keefer, 1997; La Porta et al., 1997; Paxton, 1999). We believe that each element is necessary for a country to have strong national social capital and that generalized trust and organizational memberships form a “virtuous circle”: “The more that citizens participate in their communities, the more they learn to trust others; the greater the trust that citizens hold for one another, the more likely they are to participate” (Brehm and Rahn, 1997: 1002). Our view of national social capital thus shares a key assumption with a national culture concept (e.g., Almond and Verba, 1963; Hofstede, 1980) in that both views are fundamentally concerned with the prevalence of coherent value clusters within societies and how these value clusters influence such societal outcomes as economic and political performances. However, the social capital view is divergent from the national culture concept in some significant ways. First, the national culture concept has been conceptualized typically as a “given” and thus exogenous in its influence on such outcomes as economic development (Guiso et al., 2006), whereas social capital is often conceptualized as endogeneous, meaning that cultural and institutional features can influence the levels of social capital in a given society (for an elaboration of this view, see Jackman and Miller, 1998). Thus, while the national culture argument has been used often as an ultimate causal determinant of societal outcomes, social capital is

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conceptualized as intimately and reciprocally related to cultural and institutional environments, operating as a “tool kit” that people may use in a varying degree to solve different kinds of problems (Swidler, 1986). Second, as a consequence of the first point above, social capital effects are deemed as less permanent than national cultural effects; for example, Putnam (2001) reports a significant change in the levels of social capital (defined as social trust and group membership) in the United States over the last two decades. Third, compared to the national culture concept which is concerned with all aspects of social life, social capital is concerned with a much more narrowly defined realm of social life, namely one's relationship network. Consequently, we know a lot more about the impacts of a national culture on entrepreneurial activities (for a review, see Hayton et al., 2002) than those of social capital. In the next section, we will discuss the concept of national social capital as a mechanism to permit and encourage entrepreneurial opportunity perception and weak tie investment. 3.1. Entrepreneurial opportunity perception We adopt the Kirznerian (1973) view of opportunity perception, according to which entrepreneurial opportunities arise from individuals' differential access to information. That is, people perceive opportunities by recognizing the value of new information to which they are exposed (Shane, 2000). We argue that different levels of generalized trust and breadth of formal organization memberships in the social environment are important reasons that some people are more likely to be exposed to new information and, therefore, to perceive entrepreneurial opportunities. 3.1.1. Generalized trust The literature on trust divides trust into two distinct categories: particularized trust and generalized trust. The first category is alternatively referred to as “strategic trust” (Hardin, 2002), “calculative trust” (Williamson, 1993), or “knowledge-based trust” (Yamagishi and Yamagishi, 1994). In this view, trusting decisions are based on weighing potential gain (broadly defined) if the trustee is trustworthy against potential loss if the trustee is not. Cast this way, particularized trust is grounded in having (or lacking) faith in particular people or even groups of people (Hardin, 2002). In contrast, generalized trust is about placing trust in others one does not know intimately, that is, strangers. Hence, generalized trust is alternatively referred to as “moral trust” (Uslaner, 2002) or “altruistic trust” (Mansbridge, 1999) and is seen in sociology as vital for the maintenance of cooperation in society (Parsons and Shils, 1951). Fukuyama stated the central idea behind generalized trust: “Trust arises when a community shares a set of moral values in such a way as to create regular expectations of regular and honest behavior” (1995: 153). Social capital literature on entrepreneurship has highlighted the roles both forms of trust can play in reducing transaction costs associated with searching for information and monitoring possible malfeasance (e.g., Westlund and Bolton, 2003). However, we suggest that, while trust in specific others, i.e., particularized trust, may be important at more micro-levels of social capital, the role generalized trust plays in perceiving entrepreneurial opportunities is crucial at the national level of analysis for two reasons: the free flow of information between groups and the reduction of inter-group conflict and increase of cooperation between groups. First, and most importantly, generalized trust can facilitate the free flow of information across socially disparate groups in a society. Because generalized trusters are tolerant of people who are different from themselves (Putnam, 1993; Seligman, 1997) and believe that dealing with strangers opens up opportunities more than it entails risks (Rotter, 1980), they interact with people who are different from themselves, not just with people they already know. “Generalized trust allows people to move out of familiar relationships in which trust is based on knowledge accumulated from long experience with particular people” (Brehm and Rahn, 1997: 1008). As generalized trust facilitates making casual acquaintances spanning across different social circles (crosscutting ties), such casual acquaintances are more likely to provide unique information that leads to an opportunity than are close friends in the same social circle, which is consistent with Granovetter's (1973) arguments on the strength of weak ties and Burt's (1992) concept of structural holes. Thus, Guiso et al. (2006) find that generalized trust has a positive and statistically significant impact on the probability of whether to become an entrepreneur. Hills et al. (1997) also report in an empirical study that entrepreneurs who have a network of weak ties identify significantly more opportunities than solo entrepreneurs. We thus believe that inter-group contacts between socially heterogeneous groups, facilitated by generalized trust, serve as conduits for new information that, combined with prior knowledge (Shane, 2000) and proper cognitive properties (Mitchell et al., 2000), can trigger perception of entrepreneurial opportunities in the Kirznerian alert individual. In contrast, a prominent feature of particularized trust is the tendency for in-group members to become more internally cohesive while developing stereotypes of those outside their group (Coleman, 1957). Janis (1982) posits such excessive in-group cohesion as a major contributor to groupthink. Such parochial internal orientation can prevent individual members of one group from searching for, or even from stumbling upon, new ideas from other groups, thereby decreasing the possibility for entrepreneurial opportunity perception. The second reason the role of generalized trust in perceiving entrepreneurial opportunities is crucial at the national level of analysis is that generalized trust can reduce inter-group conflict and increase cooperation at the societal level by making the proclivity for cooperation portable across disparate social groups. In doing so, generalized trust allows the society to develop without fragmenting into mutually suspicious and distrustful “fiefdoms” and, thus, helps the society to work together in creating

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and discovering entrepreneurial opportunities. To the extent that entrepreneurial opportunity perception involves joint problemsolving and collaboration among multiple stakeholders, including founding entrepreneurs (Sarasvathy et al., 2002), generalized trust contributes to opportunity perception by facilitating the processes of negotiation and collaboration across sub-groups in a society. Particularized trust, on the other hand, can contribute to cooperation only among people who know each other, so it can help reasonably small-scale intra-group collaboration, but not society-wide inter-group collaboration. Even worse, to take an extreme example from Gambetta (1988: 214), there are instances of high particularized trust, like those among the Mafia, that would have negative effects at the society level. Based on these arguments, we hypothesize as follows: Hypothesis 1. The higher the level of generalized trust in a country, the more likely a resident of that country is to perceive entrepreneurial opportunities, controlling for individual- and other national-level attributes. 3.1.2. Breadth of formal organization memberships The breadth of formal organization memberships, the extent to which one's organizational membership involves many different organizational types, can affect entrepreneurial opportunity perception in several ways. First, joining formal organizations allows people to socialize outside their immediate family and kin circles (Putnam, 1992). In particular, when such organizational activities involve many different types of formal organizations, they provide access to diverse perspectives and nonredundant information (Burt, 1997; Ibarra and Andrews, 1993). Such exposure can help entrepreneurs to recognize previously unexplored opportunities or to create new opportunities by combining prior knowledge with newly acquired information in a unique way (Shane, 2000). Hence, the broader the composition of an individual's organization membership types are, the more diverse information and the more people the individual is exposed to and the greater chance the individual has for perceiving entrepreneurial opportunities. In contrast, people who do not participate in formal organizations or who participate in a small number of formal organizations tend to focus their relationships on strong ties within dense networks of similar individuals. Since information and perspectives are likely to be redundant and less diverse in such networks, the individual is less likely to perceive or discover new opportunities. Second, weak ties generated through diverse formal organization memberships facilitate autonomy because they involve relatively infrequent interactions and low emotional closeness with the people belonging to the same organization. Thus, the individual is less likely to be pressured to conform in networks of weak ties (Perry-Smith and Shalley, 2003). This, in turn, allows the individual to define himself or herself as an autonomous individual and to take necessary risks in discovering entrepreneurial opportunities. Strong ties, in contrast, are a conduit for social influence pressures, including conformity pressures, which are generally considered to hinder entrepreneurship. Thus, Westlund and Bolton (2003) find that strong ties between individuals may well stifle entrepreneurship—that is, may discourage “marching to a different pipe” or “coloring outside the lines”—rather than encourage it (2003: 80). Third, since they put people in contact with more socially distant and diverse people, memberships in different types of formal organizations contribute to building generalized trust more than does informal socializing (Putnam, 2001). Thus, Brehm and Rahn (1997) found that people who joined formal organizations were more trusting than people who stayed at home. When people gain generalized trust through formal organization memberships, this in turn can lead to perceiving more entrepreneurial opportunities, as proposed in Hypothesis 1. Based on these arguments, we propose the following hypothesis: Hypothesis 2. The broader the types of formal organization memberships among residents in a country, the more likely a resident of that country is to perceive entrepreneurial opportunities, controlling for individual- and other national-level attributes. 3.2. Weak tie investment People's willingness to provide financial capital is crucial for entrepreneurs' success because research has shown that, even in developed nations where financial markets are more accessible, the constraint of financial capital is one of the most significant causes of small business failure (Fredland and Morris, 1976; Peterson and Shulman, 1987). Yet research has also shown that people's willingness to provide financial capital to entrepreneurs varies from society to society (Bygrave et al., 2003). In some societies, entrepreneurs rely exclusively on their family members and kin for initial and emergency financing, whereas in others, entrepreneurs can tap into investors beyond their immediate social circles based on the quality of their business plans and prospects. We call the latter weak tie investment. One way to think about such societal variation in weak tie investment has to do with the contrast between universalism and particularism (Heimer, 1992; Parsons and Shils, 1951; Pearce et al., 2000). In the context of this study, following Weber, universalism is the application of decision rules based on meritocratic criteria (making an investment solely based on an impersonal, merit-based assessment). In contrast, particularism refers to actions based on an exclusive attachment to one's own particular group. In this context, investing in other entrepreneurs because of social relationships with them (as, say, one's family members) is an example of particularism. Since residents in a society with high generalized trust are more open to trusting strangers and have more numerous weak ties, they may be more open to investing in an entrepreneur with whom they have a weak personal tie, relying on universal criteria, than are residents in a society with less generalized trust. In contrast, in-group ties are particularly strong in societies where generalized trust is not well developed (Banfield, 1958). In such societies, people may rely heavily in their economic transactions

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on known and proven personal ties and be less open to investing financial resources in an entrepreneur from an unknown group. Hence, more particularistic criteria based on strong ties may prevail in those societies. We therefore hypothesize as follows: Hypothesis 3. The higher the level of generalized trust in a country, the more likely a resident of that country is to invest in an entrepreneur with whom he or she has a weak personal tie, controlling for individual- and other national-level attributes. 4. Methodology 4.1. Data We estimated entrepreneurial opportunity perception and weak tie investment with multi-level models applied to data from the Global Entrepreneurship Monitor (GEM) project linked with social capital data from the World Values Survey (WVS) and other country-level data from multiple sources. To our knowledge, this is the first systematic cross-national empirical analysis on the topic with a sample that contains a large number of countries and individual residents. We obtained individual-level data on entrepreneurial opportunity perception and weak tie investment from the GEM project. In each participating country, the GEM project administered a standardized survey to a representative sample of adults (18– 64 years old), yielding a cross-country total of 289,308 individuals. In advanced countries where the majority of the population live in households with landline phones, the surveys are completed by phone; in countries where a small proportion of households have landline phones (such as China, India, and Uganda) a geographically stratified sampling procedure is used to locate households and respondents for face-to-face interviews. The sample size ranged from 1015 individuals in Uganda to 43,066 in the UK. In order to draw conclusions generalizable to the populations, raw data were given appropriate weights to match each country sample with the age and gender structure of the 2002 U.S. Census International Database. Though our sample included 36 countries, the actual number of respondents and countries included in our final sample varied because of individual- and countrylevel missing data. (See Tables 2 and 3 for the list of countries included in the sample.) Using population samples, the GEM project estimates the prevalence rates of opportunity perception and weak tie investment across participating countries (for details on the GEM, see Reynolds et al., 2005). We pooled data across the 3-year period of 2001, 2002, and 2003 to increase the stability of those measures, particularly for some of the smaller nations included in our sample. This strategy seemed reasonable given that the entrepreneurial opportunity perception and weak tie investment for each nation were likely to be stable in the short run. To verify this assumption, we ran an analysis of variance (ANOVA) which showed that variation within countries over time explained much less than 1% of the total variations on both dependent variables. The result suggested that our dependent variables did not vary significantly from year to year.2 To assess country-level determinants of entrepreneurial outcomes, we merged data from the WVS and other datasets with the individual-level GEM data files using the country identifiers. Data on social capital were derived from the WVS, which has 118,519 respondents from 81 countries. The majority of the surveys in this data collection were from the 1999–2001 wave, but 4 of those used in this study were from countries that were surveyed in the 1995 wave: Australia, Brazil, Norway, and Switzerland.3 We obtained other country-level measures from various sources detailed in the appendix. 4.2. Measures Our dependent variables were opportunity perception and weak tie investment. Opportunity perception was measured by asking the respondents whether there would be, in the next 6 months, good opportunities for starting a business in the area where they lived. This measure was a binary variable (1 = yes, 0 = no). To measure weak tie investment, respondents were first asked whether they had, in the past 3 years, personally provided funds for a new business started by someone else; if they said yes, they were subsequently asked the following question: “What was your relationship with the person that received your most recent personal investment?” The answers were coded as follows: 1 = close family member; 2 = some other relative, kin, or blood relation; 3 = a friend or neighbor; 4 = a work colleague; and 5 = a stranger with a good business idea.4 The answers were treated as an ordinal variable to measure the relationship distance between the parties involved. The key independent variables in our research were levels of social capital in the countries in which GEM respondents reside. Cross-national data on social capital came from the WVS which provides fairly precise measures of the two dimensions of social capital—generalized trust and breadth of formal organization memberships.5 We measured national-level social capital by aggregating individual responses from the WVS to a national scale.6 Since some groups—for example, city dwellers and the better

2 We also included in the models a survey year variable, which distinguished the year in which respondents were interviewed, to capture the effect of temporal trend; we found its effect insignificant. We also re-estimated the same models using dummy variables for each year and observed no differences in the results. 3 We conducted additional analyses excluding these 4 countries from the sample but found no substantive difference in the results. 4 The ordering is based on the standard criteria of tie strength: closeness, frequency, and duration (Marsden, 1990). We conducted additional analyses switching the coding of “a work colleague” to 3 and “a friend or neighbor” to 4 but found no substantive difference in the results. 5 The dimensions and measurement of each dimension are consistent with prior research on national social capital (e.g., Knack and Keefer, 1997; La Porta et al., 1997; Paxton, 1999). 6 Subramanian et al. (2003) found that the aggregated measure was more than a compositional artifact of individuals and could be attributed to a collective/ contextual construct at the country level.

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educated—were oversampled in the WVS, to make our sample nationally representative, we used the weight variable provided in the data when computing country-level means. To measure generalized trust, we used the percentage of individuals in each country who believed that others could be trusted (from the following question: “Generally speaking, would you say that most people can be trusted or that you need to be very careful in dealing with people?”). We agree with Uslaner's (2002) assertion that the idea of generalized, as opposed to particularized, trust is well captured by asking one's attitude toward “most people,” understanding that even the most trusting person will recognize that some people should not be trusted. Also consistent with the definition of generalized trust, the question makes no mention of context. As a validity check, we correlated the trust score with the number of wallets, reported in Knack and Keefer's (1997) study, that were lost and subsequently returned by strangers with their contents intact in each of 20 cities, selected from 14 different Western European countries, and found that the generalized trust score was correlated at 0.67. We also found that our measure of generalized trust from the 1990 WVS was correlated weakly at 0.06 with the “trust in family members” measure from the same WVS.7 Additionally, using the 2000 WVS, generalized trust was found to be negatively correlated at − 0.61 with the traditionalism index8 of the country and at −.43 with the ethnocentrism scale.9 All of these give us some confidence that the WVS trust measure primarily captures generalized trust, as opposed to particularized trust placed in people with whom one has repeated interactions. We also compared the WVS trust measure with other comparable measures. First, we obtained a similarly worded trust measure from the Eurobarometer 1996 survey and compared it with the score from a subset (n = 12) of the WVS sample countries that also participated in the Eurobarometer survey. We found the correlation score acceptable (0.62). Second, because trust seems to decline with partial democratization but to increase with full democracy (Uslaner, 2002), we created a dummy measure of “continuous democracy” (1 = more than 46 consecutive years of democracy since 1950; 0 = otherwise) and found its correlation with the WVS measure of trust acceptable (0.62). Finally, we believe that using the social capital measure from a single year, 2000, to explain the dependent variables measured in a period of 3 years is acceptable because La Porta et al. (1997) found that, using the same trust measure as the one we used in this study, the correlation across countries between trust in the 1980s and in the 1990s was high (0.91). We measured the breadth of formal organization memberships by averaging the number of different types of voluntary organization memberships (e.g., in religious organizations, social welfare services, education, arts, music or cultural activities, trade unions, environmental groups, and professional associations) of individuals in a country from the WVS.10 To minimize the possibility of drawing misleading conclusions about the hypothesized social capital effects, we incorporated several control variables at the country level: the natural log of Gross Domestic Product (GDP) per capita (constant 2000 US$) from the previous year of the GEM survey, GDP per capita growth from the previous year to the year of the GEM survey (annual percentage), ethnic and cultural diversity, availability of institutional loans, and legal origin. The first two control variables are often included in country-level studies of entrepreneurship (e.g., Carree, 2002; Wong et al., 2005) and increase confidence in our assessment of the hypotheses evaluated in the study. We used lagged measures of these variables because a contemporaneous measure might include changes that occurred after the date of the survey.11 We also controlled for the ethnic and cultural diversity of the country because ethnically and culturally diverse societies can either increase generalized trust at the societal level due to the increased contact among different groups or decrease generalized trust through ethnocentrism. Though we don't have a theoretical prediction in either direction, since it can potentially influence our Hypothesis 1, we controlled for the effect of the diversity by using a measure developed by Fearon (2003). In addition, because this institutional mechanism may provide alternatives for generalized trust, especially for our Hypothesis 3, we also included an index measuring the availability of institutional loans from the Executive Opinion Survey summarized in the Global Competitiveness Report (World Economic Forum, 2000) as well as dummies for a legal origin of the countries. We also controlled directly for the type of legal institutions operating across different countries that may influence investment in weak ties, using La Porta and his colleagues' classification system (Djankov et al., 2003): We expected that, in countries with a legal system that protects the rights of the investor to a higher extent (e.g., English common law, Scandinavian and German law), entrepreneurs would turn to institutional loans, rather than to family members or friends, thereby decreasing the number of investment in weak ties. Finally, to isolate the effects of these country-level predictors, we included well-established individual-level correlates of entrepreneurial opportunity perception as control variables in our analysis. Our measurement of control variables conformed closely to strategies used in prior research (see the appendix for a more detailed description of the control variables).

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Unfortunately, we were not able to replicate this with the 1995 or 2000 WVS because the WVS subsequently dropped the item on “trust in family members.” The traditionalism index emphasizes the following: God is very important in respondent’s life; it is more important for a child to learn obedience and religious faith than independence and determination; abortion is never justifiable; respondent has strong sense of national pride; respondent favors more respect for authority. 9 This scale is a percentage of people who answered that they would not like to have immigrants/foreign workers, people who have AIDS, or homosexuals as neighbors. 10 A limitation of this measure is that, if respondents have multiple memberships of the same type, these are counted only once. Hence, this indicator does not measure the intensity of participation in organizations. Although the extensive set of categories reduces the likelihood that any two organizations fall in the same category, our assumption that organization memberships are correlated with levels of activity needs further investigation, and this limitation should be kept in mind when interpreting the results. 11 We also estimated all models shown using averaged data for 5 years instead of data for a single year. The results obtained from these analyses (not shown) were very similar to those reported. 8

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4.3. Analytic strategy Our analysis for the first dependent variable, entrepreneurial opportunity perception, used probit regression models because of its binary response options.12 We began by first entering the generalized trust variable along with individual-level attributes (Model 1 in Table 2) to account for the possibility that levels of entrepreneurial opportunity perception might vary across nations simply as a function of the nonrandom distribution of the population. Specifically, countries with high opportunity perception might be those with relatively large numbers of people with the individual attributes that have been linked with those outcomes. If we still found the effect of generalized trust when controlling for individual differences, this would suggest that the effect was more than the compositional effect of individual characteristics. We then assessed whether our other country-level predictors affected the impact of generalized trust on entrepreneurial opportunity perception, controlling for individual-level attributes (Models 2–5 in Table 2). We also ran Two-Stage Least Squares (2SLS) to correct for potential endogeneity and reverse causality (Model 6 in Table 2). Conceivably, highly entrepreneurial societies can produce more trusting citizens with membership in broader types of organizations. If a high level of entrepreneurial opportunity perception increases social capital, our Probit regression estimates could be biased upwards. Corrections for endogeneity of social capital to entrepreneurial opportunity perception require exogenous instruments for the social capital variables. We used the percentage of Protestants as an instrument variable for social capital.13 This instrument is extremely effective in explaining cross-nation differences in social capital in first-stage regressions. For example the other right-hand-side variables in the model, in the absence of the instrument, explain 24% of the variation in generalized trust. With the addition of this instrument, 43% of the variation is explained. This instrument is valid not only in the sense that it is a powerful predictor of social capital, but also in the sense that it does not influence entrepreneurial opportunity perception independently of its effect on social capital. In results not shown here, but available from the authors, the Smith– Blundell test for effects of endogeneity failed to reject the null hypothesis that the instrument does not belong directly in the entrepreneurial opportunity perception equation. We then repeated the same procedures with the second social capital variable, breadth of formal organizational membership (Models 7–12 in Table 2). The second dependent variable, the probability of weak tie investment, was measured on an ordinal scale and thus was estimated with ordered logit models (proportional odds models). An ordered logit model makes use of the ordered nature of the response levels without being influenced by the numerical values used for the dependent variable.14 In performing our statistical analysis with all models, we used the cluster option in Stata's estimation command to obtain a robust variance estimate that adjusts for within-cluster correlation (Williams, 2000; Wooldridge, 2002).15 It acknowledges that individuals in a nation may be more similar to each other than to those in other nations. 5. Results Table 1 presents descriptive statistics and a correlation matrix for all of the variables included in the analysis. The national rate of individuals perceiving entrepreneurial opportunities averaged 29% across the 36 countries in our sample, ranging from a low of 6% in Japan to a high of 65% in Uganda. There was also a significant cross-country variation in the mean value of weak tie investment. Countries like Greece and Portugal, for example, had the lowest scores on weak tie investment, while countries like Switzerland and Finland had the highest scores in our sample. This prompts the question of what factors might account for differences in levels of those variables across countries. Models 1–12 of Table 2 explored this question. Models 1 and 7 included all of the individual-level control variables, plus the social capital variables. Because of a somewhat high correlation between the two measures of social capital, we entered each separately. The most important findings shown in these models revealed that the estimated effects of the level of social capital (Hypotheses 1 and 2) were in the expected direction and were statistically significant. Given the nonlinearity of the probit model, the relative magnitudes of raw probit coefficients were not directly interpretable. To interpret the coefficients more intuitively, we calculated changes in the predicted probabilities (using the prchange command developed by Long and Freese, 2001) and found that a standard deviation change in generalized trust centered on the mean increased the probability of perceiving entrepreneurial opportunities by 3%, holding other variables to their means. Similarly, a standard deviation change in breadth of formal organization memberships increased the probability by 2%. Figs. 1 and 2 present predicted probabilities of entrepreneurial opportunity perception for respondents who reside in countries that differ substantially along these dimensions. In each case, the predicted probabilities were computed using the coefficients from Models 1 and 7 of Table 2 and assuming mean values for all other variables (see, e.g., Hosmer and Lemeshow, 2000). The predicted probabilities associated with the estimated trust effect implied that levels of entrepreneurial opportunity perception ranged from about 20% in areas with a very low trust rate (the 10th percentile) to about 39% in areas with a very high trust rate (the 60th percentile), assuming mean values for all other variables (including the other country-level predictors). We

12

Our main findings did not change across OLS models and probit models. Religious composition has been used as exogenous instrument for social capital, following La Porta et al. (1997) and Zak and Knack (2001). 14 We also ran the analyses with other estimation methods, such as OLS and multinomial logit, and found our results essentially stable. 15 We also repeated the same analyses using hierarchical linear models and found no substantive difference in the results. Minimal differences were observed between robust and ordinary standard errors in the hierarchical linear modeling results. 13

0.29 2.30 1.53 43.85 0.59 0.01 0.29 0.38 0.29 0.03 0.33 0.38 0.29 0.34 0.41 0.33

1. Opportunity perception 2. Weak tie investment 3. Female 4. Age 5. Work status 6. No education 7. Some secondary education 8. Secondary degree 9. Post secondary education 10. Graduate degree 11. Income (Lowest 33%) 12. Income (Middle 33%) 13. Income (Upper 33%) 14. Knowing other entrepr. 15. Confidence in one's skills 16. Fear of failure

Mean

32.40 1.16 9.23 2.08 0.27 4.23 28.19 0.43 0.08 0.23 0.16 0.1

1. Generalized trust 2. Breadth of formal org. membership 3. Ln(GDP) 4. GDP growth 5. Diversity 6. Availability of institutional loans 7. % of Protestants 8. English legal origin 9. Socialist legal origin 10. French legal origin 11. German legal origin 12. Scandinavian legal origin

0.45 1.36 0.50 16.58 0.49 0.10 0.45 0.49 0.45 0.17 0.47 0.49 0.45 0.47 0.49 0.47

S.D.

Variable

Country level, N = 36

Mean

Variable

Individual level, N = 289,308

16.61 0.83 1.20 3.28 0.20 0.80 32.34 0.5 0.28 0.42 0.37 0.3

S.D.

− 0.08⁎ − 0.06⁎ 0.09⁎ b 0.005 − 0.05⁎ − 0.05⁎ 0.08⁎ 0.04⁎ − 0.06⁎ − 0.02⁎ 0.08⁎ 0.22⁎ 0.22⁎ − 0.03⁎

1

0.04⁎ − 0.16⁎ 0.02⁎ 0.01⁎ 0.02⁎ − 0.02⁎ − 0.03⁎ 0.09⁎ − 0.01⁎ − 0.08⁎ − 0.12⁎ − 0.18⁎ 0.06⁎

3

0.45⁎ 0.44⁎ 0.04 − 0.26 0.41⁎ 0.61⁎ − 0.2 − 0.16 − 0.18 0.07 0.63⁎

1

− 0.21⁎ − 0.14⁎ 0.13⁎ − 0.01 − 0.02 − 0.05⁎ 0.06⁎ 0.01 − 0.06⁎ − 0.06⁎ 0.10⁎ 0.03⁎ 0.06⁎ − 0.02

2

Table 1 Descriptive statistics for opportunity perception and weak tie investment.

0.33 − 0.06 0.06 0.47⁎ 0.67⁎ 0.02 − 0.27 − 0.08 − 0.06 0.4⁎

2

− 0.26⁎ 0.05⁎ 0.11⁎ − 0.04⁎ − 0.09⁎ 0.01⁎ 0.15⁎ − 0.05⁎ − 0.10⁎ − 0.16⁎ − 0.04⁎ − 0.05⁎

4

− 0.22 − 0.46⁎ 0.68⁎ 0.43⁎ 0.04 − 0.44⁎ − 0.1 0.2 0.24

3

− 0.05⁎ − 0.16⁎ − 0.01⁎ 0.15⁎ 0.07⁎ − 0.28⁎ 0.07⁎ 0.22⁎ 0.17⁎ 0.20⁎ 0.02⁎

5

− 0.50⁎ − 0.41⁎ − 0.11⁎ 0.17⁎ − 0.01⁎ − 0.16⁎ − 0.08⁎ − 0.10⁎ 0.05⁎

7

0.10 0.07 − 0.11 0.08 0.42⁎ − 0.19 − 0.17 − 0.05

4

− 0.07⁎ − 0.08⁎ − 0.07⁎ − 0.02⁎ 0.06⁎ − 0.03⁎ − 0.03⁎ − 0.03⁎ − 0.03⁎ − 0.01⁎

6

− 0.02 0.01 0.5 − 0.12 − 0.04 − 0.37 − 0.23

5

− 0.50⁎ − 0.14⁎ 0.03⁎ 0.05⁎ − 0.08⁎ − 0.03⁎ − 0.02⁎ b0.005

8

0.62⁎ 0.53⁎ − 0.39 − 0.28 − 0.31 0.2

6

− 0.11⁎ − 0.18⁎ − 0.02⁎ 0.20⁎ 0.11⁎ 0.11⁎ − 0.04⁎

9

0.25 − 0.36 − 0.5⁎ − 0.09 0.68⁎

7

− 0.08⁎ − 0.05⁎ 0.14⁎ 0.04⁎ 0.07⁎ − 0.02⁎

10

− 0.50⁎ − 0.01⁎ − 0.02⁎ 0.02⁎

12

− 0.26 − 0.47⁎ − 0.38 − 0.29

8

− 0.55⁎ − 0.45⁎ − 0.13⁎ − 0.12⁎ 0.02⁎

11

− 0.16 − 0.13 − 0.1

9

0.14⁎ 0.14⁎ − 0.05⁎

13

− 0.23 − 0.18

10

0.27⁎ − 0.01⁎

14

− 0.15

11

− 0.11⁎

15

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Table 2 Models of entrepreneurial opportunity perception. (1)

(2)

Survey year

0.11* 0.11* (0.05) (0.05) Female − 0.10*** − 0.10*** (0.02) (0.02) Age b−0.005*** b−0.005*** (b0.005) (b 0.005) Knowing other 0.39*** 0.39*** entrepr. (0.03) (0.03) Confidence in 0.46*** 0.46*** one's skill (0.04) (0.04) Fear of failure − 0.04 − 0.04 (0.04) (0.04) Work status b− 0.005 b 0.005 (0.03) (0.03) Income lowest 0.01 b 0.005 33% (0.04) (0.03) Income upper 0.09*** 0.09*** 33% (0.02) (0.02) No education − 0.19 − 0.21 (0.23) (0.21) Some secondary 0.04 0.04 edu (0.05) (0.05) Post secondary 0.15*** 0.15*** edu (0.03) (0.03) Grad. degree 0.24*** 0.24*** (0.04) (0.04) Generalized trust 0.01*** 0.01*** (b0.005) (b 0.005) Breadth of formal org. membership Ln(GDP) − 0.02 (0.04) GDP growth

(3)

− 1.29*** (0.15) Log − 59253 pseudolikelihood # of Respondents 105180 # of Countries 36 a

(5)

(6)

0.08 0.06 (0.05) (0.06) − 0.11*** − 0.13*** (0.03) (0.02) b−0.005*** b−0.005*** (b0.005) (b 0.005) 0.40*** 0.39*** (0.03) (0.03) 0.44*** 0.43*** (0.05) (0.05) − 0.02 − 0.03 (0.04) (0.04) b 0.005 −0.01 (0.04) (0.04) b 0.005 b− 0.005 (0.04) (0.04) 0.07*** 0.09*** (0.02) (0.02) − 0.14 − 0.18 (0.19) (0.27) 0.04 0.03 (0.04) (0.05) 0.15*** 0.17*** (0.03) (0.04) 0.21*** 0.23*** (0.03) (0.04) 0.01*** 0.02** (b0.005) (0.01)

(7)

(9)

(10)

(11)

0.10 0.10 (0.06) (0.06) − 0.10*** − 0.10*** (0.02) (0.02) b−0.005** b−0.005*** (b 0.005) (b0.005) 0.40*** 0.40*** (0.04) (0.04) 0.42*** 0.42*** (0.05) (0.05) − 0.04 − 0.04 (0.04) (0.04) 0.04 0.04 (0.04) (0.04) 0.01 0.01 (0.03) (0.03) 0.07* 0.07* (0.03) (0.03) − 0.21 − 0.21 (0.14) (0.16) 0.03 0.03 (0.05) (0.05) 0.15*** 0.15*** (0.04) (0.04) 0.24*** 0.24*** (0.05) (0.05)

(8)

0.11 (0.06) − 0.10*** (0.02) b−0.005*** (b 0.005) 0.40*** (0.04) 0.42*** (0.05) − 0.04 (0.04) 0.04 (0.04) 0.01 (0.03) 0.07** (0.03) − 0.20 (0.15) 0.02 (0.04) 0.15*** (0.04) 0.25*** (0.05)

0.10 (0.05) − 0.10*** (0.03) b−0.005*** (b0.005) 0.40*** (0.03) 0.42*** (0.05) − 0.04 (0.04) 0.04 (0.04) 0.01 (0.03) 0.07** (0.03) − 0.19 (0.15) 0.01 (0.04) 0.15*** (0.04) 0.25*** (0.05)

0.08 0.05 (0.05) (0.08) − 0.11*** − 0.14*** (0.03) (0.02) b−0.005*** b−0.005** (b0.005) (b0.005) 0.41*** 0.35*** (0.03) (0.05) 0.42*** 0.39*** (0.05) (0.05) − 0.03 − 0.02 (0.04) (0.05) 0.04 0.01 (0.04) (0.04) 0.01 − 0.02 (0.04) (0.04) 0.06** 0.08** (0.02) (0.03) − 0.15 − 0.41 (0.17) (0.25) 0.03 b 0.005 (0.04) (0.04) 0.16*** 0.14* (0.04) (0.06) 0.22*** 0.23** (0.05) (0.08)

(12)

0.15* (0.06)

0.15* (0.07)

0.15* (0.07)

0.15* (0.07)

0.11* (0.05)

0.48* (0.27)

b− 0.005 (0.05)

− 0.02 (0.05) − 0.02 (0.02)

− 0.02 (0.05) − 0.02 (0.02) 0.03 (0.29)

− 0.13 (0.07) − 0.03 (0.02) − 0.30 (0.30) 0.22** (0.08)

− 0.21* (0.09) − 0.02 (0.02) − 0.83* (0.39) 0.13 (0.21)

− 0.04 (0.04) − 0.02 (0.02)

− 0.04 (0.03) − 0.03 (0.02) 0.42 (0.23)

− 0.11 (0.06) − 0.03 (0.02) 0.11 (0.24) 0.16* (0.08)

− 0.14 (0.07) − 0.04** (0.02) 0.17 (0.27) 0.15 (0.09)

− 1.14** (0.44) − 59246

− 0.87* (0.39) − 59196

− 1.09** (0.37) − 57711

− 0.97* (0.39) − 55164

− 0.68 (0.43) − 391536

− 1.12*** − 1.12* (0.17) (0.52) − 57809 − 57809

− 0.92 (0.53) − 57782

− 0.93 (0.55) − 56448

− 0.65 (0.54) − 53799

0.40 (0.81) − 136774

105180 36 a

105180 36 a

103224 35 b

99076 32 c

87038 28 d

102143 34 e

102143 34 e

100187 33 f

96039 30 g

86176 27 h

Diversity Availability of institutional loans Constant

(4)

0.11* 0.11* (0.05) (0.05) − 0.10*** − 0.10*** (0.02) (0.02) b−0.005*** b−0.005*** (b0.005) (b0.005) 0.39*** 0.40*** (0.03) (0.03) 0.45*** 0.45*** (0.04) (0.05) − 0.04 − 0.03 (0.04) (0.04) b 0.005 b 0.005 (0.03) (0.04) 0.01 b 0.005 (0.03) (0.04) 0.09*** 0.09*** (0.02) (0.02) − 0.19 − 0.19 (0.21) (0.19) 0.03 0.03 (0.05) (0.04) 0.15*** 0.13*** (0.03) (0.03) 0.25*** 0.22*** (0.05) (0.04) 0.01*** 0.01*** (b0.005) (b0.005)

102143 34 e

Robust standard errors in parentheses. We used one-tailed tests for hypothesized relationships. ***p b 0.001, **p b 0.01, *p b 0.05. a The countries included in the full sample were: South-Africa, France, Italy, Russian Federation, New Zealand, Mexico, Brazil, Norway, Australia, Belgium, Netherlands, India, United Kingdom, Portugal, Finland, Japan, Croatia, Spain, Greece, Switzerland, Canada, Denmark, Iceland, Slovenia, Poland, Germany, Argentina, Singapore, United States of America, Israel, Hungary, People's Republic of China, Uganda, Chile, South Korea, and Sweden. b Iceland was dropped from the full sample due to a missing value. c Iceland, Croatia, Slovenia, and Uganda were dropped from the full sample due to missing values. d Iceland, Croatia, Slovenia, Uganda, Spain, Singapore, Israel, and South Korea were dropped from the full sample due to missing values. e Israel and New Zealand were dropped from the full sample due to missing values. f Iceland, Israel, and New Zealand were dropped from the full sample due to missing values. g Israel, New Zealand, Iceland, Croatia, Slovenia, and Uganda were dropped from the full sample due to missing values. h Israel, New Zealand, Iceland, Croatia, Slovenia, Uganda, Spain, Singapore, and South Korea were dropped from the full sample due to missing values.

also found that the breadth of formal organization memberships exhibited an effect of similar magnitude on opportunity perception. Models 1 and 7 in Table 2 also included individual-level attributes shown in prior research to be related to entrepreneurial opportunity perception. The results showed that males, individuals with higher education and family incomes, and those who knew personally someone who had started a business, or those who believed that they had the knowledge, skill, and experience required to start a new business, were significantly more likely to perceive entrepreneurial opportunities. These results are highly consistent with an extensive body of prior research on entrepreneurial opportunity perception (Javier et al., 1997; Reynolds, 1997).

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Fig. 1. Plot of predicted probabilities (with 95% Confidence Interval) of entrepreneurial opportunity perception for generalized trust.

Models 2, 3, 8, and 9 showed that the level of economic development (measured by GDP per capita) and the economic growth rate (measured by the annual change in GDP per capita) did not exert significant effects on entrepreneurial opportunity perception. Ethnic and cultural diversity was significantly and negatively related to entrepreneurial opportunity perception in only one specification (Model 12). Consistent with an argument that institutional environment, such as the availability of venture capital and bank loans, do matter in entrepreneurial activities (Guiso et al., 2004), we found that the availability of institutional loans did increase entrepreneurial opportunity perception (Models 5 and 11). However, even after controlling for the availability of institutional loans, the effects of social capital were still significant. The 2SLS estimates of social capital's effect (Models 6 and 12) were consistent with the Probit regression estimates. Because Probit (and Probit IV) estimates are scaled by the standard error of the error term and this might implicitly differ between the

Fig. 2. Plot of predicted probabilities (with 95% Confidence Interval) of entrepreneurial opportunity perception for formal orgmemberships.

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325

two models, the parameter estimates cannot typically be compared to those of the simple Probit estimates. One can, however, compare marginal effects. The marginal effect of generalized trust implied by the Probit IV estimates is 0.02, compared to that of Probit estimates, 0.004. Similarly, the marginal effect of formal organizational membership by the Probit IV estimates is much bigger (0.48) than that of Probit estimates, 0.04. These results strongly support the interpretation that causality runs from social capital to entrepreneurial opportunity perception rather than from entrepreneurial opportunity perception to social capital. Table 3 shows that generalized trust increased the chance of investing in an entrepreneur with whom one had a weak tie, and this effect is consistent across different model specifications (Models 1–7). For a standard deviation increase in trust, the Table 3 Models of weak tie investment.

Survey year Female Age Knowing other entrepr. Confidence in one's skill Fear of failure Work status Income lowest 33% Income upper 33% No education Some secondary edu Post secondary edu Grad. degree Generalized trust

(1)

(2)

(3)

(4)

(5)

(6)

(7)

− 0.12* (0.05) − 0.74*** (0.10) − 0.01** (b0.005) − 0.02 (0.09) 0.08 (0.10) 0.01 (0.12) 0.18 (0.12) − 0.11 (0.13) 0.19** (0.07) 0.10 (0.25) 0.06 (0.20) 0.09 (0.08) 0.32 (0.25) 0.02*** (b0.005)

− 0.10* (0.05) − 0.74*** (0.10) − 0.01** (b 0.005) 0.01 (0.10) 0.08 (0.10) 0.01 (0.12) 0.17 (0.12) − 0.07 (0.12) 0.19** (0.07) 0.34 (0.27) 0.11 (0.18) 0.08 (0.08) 0.33 (0.26) 0.01*** (b 0.005) 0.12* (0.06)

− 0.11* (0.05) − 0.74*** (0.10) − 0.01** (b 0.005) b 0.005 (0.10) 0.09 (0.10) 0.01 (0.12) 0.17 (0.12) − 0.08 (0.12) 0.18** (0.07) 0.30 (0.26) 0.11 (0.18) 0.08 (0.08) 0.32 (0.26) 0.01** (b 0.005) 0.15** (0.06) 0.02 (0.02)

− 0.10* (0.05) − 0.72*** (0.10) − 0.01** (b0.005) − 0.05 (0.09) 0.10 (0.10) − 0.02 (0.12) 0.17 (0.12) − 0.04 (0.12) 0.18* (0.07) 0.20 (0.27) 0.10 (0.17) 0.14 (0.08) 0.39 (0.24) 0.01* (b0.005) 0.13** (0.05) 0.03 (0.03) − 0.80* (0.37)

− 0.11 (0.06) − 0.77*** (0.10) − 0.01** (b0.005) − 0.05 (0.10) 0.12 (0.10) 0.01 (0.14) 0.12 (0.13) b 0.005 (0.13) 0.22** (0.07) 0.30 (0.30) 0.12 (0.16) 0.13 (0.07) 0.45 (0.25) 0.01** (b0.005) 0.28* (0.11) 0.04 (0.03) − 0.55 (0.44) − 0.19 (0.14)

− 0.04 (0.04) − 0.79*** (0.10) − 0.01** (b 0.005) − 0.09 (0.11) 0.14 (0.1) − 0.02 (0.13) 0.14 (0.13) 0 (0.13) 0.18** (0.07) 0.2 (0.29) 0.06 (0.13) 0.20* (0.08) 0.47* (0.23) 0.01* (0.01) 0.06 (0.11) − 0.01 (0.03) 0.13 (0.26) 0.09 (0.15) 0.59 (0.32) − 0.29 (0.15) 0.70*** (0.2) 0.22 (0.24)

− 4865 3554 36 b

− 4857 3554 36 b

− 4856 3554 36 b

− 4690 3446 35 c

− 4440 3244 32 d

− 4411 3244 32 d

− 0.06 (0.05) − 0.81*** (0.11) − 0.01** (b0.005) − 0.06 (0.1) 0.14 (0.11) − 0.03 (0.14) 0.13 (0.13) 0.03 (0.13) 0.22*** (0.06) 0.18 (0.28) 0.08 (0.12) 0.17* (0.07) 0.42+ (0.24) 0.01** (0.01) 0.11 (0.12) − 0.01 (0.03) 0.23 (0.29) 0.04 (0.17) 0.48 (0.35) − 0.34* (0.17) 0.61** (0.24) 0.12 (0.26) − 0.09 (0.07) − 4246 3132 30 e

Ln(GDP) GDP growth Diversity Availability of institutional loans Socialist legal tradition French legal tradition German legal tradition Scandinavian legal tradition Breadth of formal org. membership Log pseudolikelihood # of Respondents a # of Countries

Robust standard errors in parentheses. We used one-tailed tests for hypothesized relationships. ***p b 0.001, **p b 0.01, *p b 0.05. a The number of respondents for weak tie investment is lower than that for entrepreneurial opportunity perception because the question was addressed only to those who had, in the past 3 years, personally provided funds for a new business started by someone else. b The countries included in the full sample were South-Africa, France, Italy, Brazil, Croatia, Russian Federation, Japan, Portugal, India, Australia, United Kingdom, Poland, Belgium, Netherlands, Mexico, Hungary, New Zealand, Israel, Norway, Finland, Canada, Spain, Argentina, Greece, Sweden, Slovenia, Singapore, Denmark, Germany, Chile, Switzerland, Iceland, United States of America, South Korea, People's Republic of China, and Uganda. c Iceland was dropped from the full sample due to a missing value. d Iceland, Croatia, Slovenia, and Uganda were dropped from the full sample due to missing values. e Iceland, Croatia, Slovenia, Uganda, New Zealand, and Israel were dropped from the full sample due to missing values.

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Fig. 3. Plot of predicted probabilities of weak tie investment for the ordered logit model. Note: The vertical line marks the average value of generalized trust in the sample.

probability of investing in a close family member decreased by 5%, and that of investing in a stranger with a good business idea increased by 2%, holding other variables constant at their means. Despite the influence of generalized trust, it is important to point out, as shown in Fig. 3, that individuals in all nations, regardless of the level of generalized trust, were more likely to invest in a close family member than in a stranger. Table 3 also included individual-level attributes for the weak tie investment variable and found that women tended to invest in their close ties, often family or kin, to a larger extent than did men. This is consistent with a previous finding in a 4-country study that female entrepreneurs had more family in their networks than did males (Greve and Salaff, 2003). Also, younger investors and those with high household income tended to a greater extent to invest in an entrepreneur with whom they had a weak tie. Among the country-level variables, we found the GDP per capital is positively associated with weak tie investment. 6. Discussion The entrepreneurship literature acknowledges that opportunity perception and weak tie investment may be shaped by factors at multiple levels. However, few studies have empirically examined the simultaneous effects of individual- and country-level factors on these phenomena. Our study found that individual-level attributes exerted significant effects on opportunity perception and weak tie investment, but the magnitude of the effects of social capital at the country level was nontrivial. What the findings suggested at the individual level was that people who perceive entrepreneurial opportunities or invest in a weak tie share common personal attributes that are distinct from those who do not, regardless of their national context. At the same time, the findings also provided support for the hypothesized contextual effects of social capital at the national level: even after controlling for individual level attributes, we found significant effects of social capital at the country level. The findings have an important implication for theories of entrepreneurship. To date, major theories have focused on the role of individual entrepreneurs in discovering or recognizing opportunities (for reviews, see Ardichvili et al., 2003; Gaglio, 1997). For example, Khilstrom and Laffont's (1979) neoclassical equilibrium model and psychological theories (e.g., McClelland, 1961) stressed fundamental attributes of individual entrepreneurs in explaining entrepreneurial opportunity perception. Austrian economists also focused on an individual entrepreneur's alertness (Kirzner, 1997) or prior experience and education (Shane, 2000). While our study found individual level effects, it extends these individual-level theories by suggesting that the social context in which an entrepreneur is embedded, especially social capital at the country level, is an additional and important contributor to entrepreneurship. Hence, our study suggests that entrepreneurial activities are jointly determined by the individual —as well as the contextual-level factors. Unfortunately, however, existing literature in the entrepreneurship research has not paid much attention to the degree to which social capital at the individual level and social capital at the country level complement each other in their joint effects on entrepreneurial opportunity perception and weak tie investment. It is reasonable to speculate that the effects of individual-level social capital on entrepreneurial opportunity perception would be stronger in nations with low levels of

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national social capital. Previous research suggests that particularized personal ties are very important in business relationships in countries without stable legal and regulatory environments (Redding, 1990; Xin and Pearce, 1996) or generalized trust (Putnam, 1992). Future study can examine whether this holds for entrepreneurship. Alternatively, researchers might study whether a high level of social capital at the country level compensates for a lack of social capital at the individual level. For example, consistent with a large body of research on entrepreneurship, we found that gender was one of the strongest predictors of entrepreneurial opportunity perception and weak tie investment, with females significantly less likely to report that they perceived entrepreneurial opportunities or invested in a stranger's good idea. Although there may be multiple reasons for this, females in many societies may have a lower level of social capital at the individual level, which in turn may contribute both to their lack of opportunity perception and to their reliance on strong ties. If this is the case, high societal levels of generalized trust and organizational memberships may compensate for the lack of individual-level social capital. Thus, the gender gap may be narrower in a society with a high level of generalized trust and dense organization memberships than in a society without these attributes. Pursuing these types of questions will advance considerably our understanding of how social capital at the individual and country levels affects entrepreneurial opportunity perception and weak tie investment. Our study also provides two important methodological advances. First, past research hinted at the possibility of crossnational variation in opportunity perception and weak tie investment but never evaluated it systematically. To our knowledge, this study offers the first empirical test using information on entrepreneurship in multiple countries including some economic, social, and institutional features of each. It thus contributes to a growing literature on the country-level determinants of entrepreneurship, such as GDP (Carree et al., 2002; Tang and Koveos, 2004), unemployment rate (Carree, 2002), market opportunities (Begley et al., 2005), governments (Jennifer et al., 2005) and financial institutions (George and Prabhu, 2000). Second, our paper contributes to multi-level research that explores micro and macro factors simultaneously as they influence cross-country variations in entrepreneurship. Unlike previous studies in international entrepreneurship, which tended to emphasize either a macro perspective (e.g., government policy, capital, legal markets, and technology) or a micro perspective (e.g., entrepreneurs' motives, goals, cognitions, skills, traits, age, gender, and race), our study included variables from both perspectives, as well as a sufficiently large number of countries and a nationally representative sample of individual residents in each country for multi-level analysis. While this study provides initial evidence as to whether social capital at the country level affects entrepreneurship, there are some important limitations of the present analysis. First, though we tried to address the issue of unobserved heterogeneity in country-level factors by including multiple control variables and using the 2SLS regressions, we were not able to provide a stronger test of the robustness of our results, such as using a dummy variable for each country because our social capital variables did not vary much within a country. Since the levels of social capital within a country do not change much in a short term,16 in order to carry out a fixed effect model, future studies will need panel data on social capital variables for a substantial period. Second, our measures of social capital were significantly correlated with broad cultural characteristics measured by Hofstede (1980). Specifically, both generalized trust and formal organization memberships are associated with high individualism, low uncertainty avoidance, and high power-distance, which in turn have been found to be related to entrepreneurial activities in cross-cultural research (Hayton et al., 2002). This raises the question of whether our results are truly driven by social capital or national cultural effects. Given their conceptual closeness and high empirical correlations, in order to tease out the individual effects of each, we would need a much larger sample of countries varying simultaneously on both dimensions. Third, a small country sample in this study also meant that the developmental variation of the country sample was somewhat limited. Most of the countries come from Western or Eastern Europe, with a few countries from South America. Africa, the Middle East, and Asia remain underrepresented in the sample. To make sure that we are not describing the effects in developed countries only, we split the sample into 23 developed (Australia, Belgium, Canada, Denmark, Finland, France, Germany, Greece, Iceland, Israel, Italy, Japan, Netherlands, New Zealand, Norway, Portugal, Singapore, South Korea, Spain, Sweden, Switzerland, United Kingdom, and U.S.) and 13 developing countries (Argentina, Brazil, Chile, Croatia, Hungary, India, Mexico, People's Republic of China, Poland, Russian Federation, Slovenia, South Africa, and Uganda). While all of the proposed hypotheses were still supported in the sub-sample of developed countries, the generalized trust variable lost significance in the sub-sample of developing countries. We speculated that this might be due to the possibility that our measure of the generalized trust could vary from a developing country to a developed country; that is, in a more inward or traditional country, dominated by family and extended family, the respondents might not be able to visualize beyond their particular trust circumstances. To examine this concern, we again split the sample into countries that scored high on the traditionalism scale in the WVS and those that scored low. However, our findings were consistent in both sub-samples. Thus, future studies need to examine why the effect of generalized trust is stronger among developed countries. Finally, the implications of our results are limited to explaining the initial phases of entrepreneurship: perceiving opportunities and investing. Further study could examine the effects of social capital on the decision to exploit entrepreneurial opportunities and on modes of exploitation (Shane and Venkataraman, 2000). Research might investigate whether social capital can explain crossnational variations in such outcomes as self-employment and business startup rates.

16

The correlation of generalized trust from the 1980 to 2000 WVS waves was 0.79, suggesting that changes in trust over time are very small.

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Appendix A. Variables used in the study

Individual-level variables Opportunity perception Weak tie investment

Survey year

Age Female Education

Work status Household income Knowing other entrepreneurs Confidence in one's skills Fear of failure

Data source Respondents were asked whether there would be, in the next 6 months, good opportunities for starting a business in the area where they lived. This measure was a binary variable (1 =yes, 0= no). Respondents were first asked whether they had, in the past 3 years, personally provided funds for a new business started by someone else; if they said yes, they were subsequently asked the following question: “What was your relationship with the person that received your most recent personal investment?” The answers were coded as follows: 1 =close family member; 2= some other relative, kin, or blood relation; 3=a friend or neighbor; 4 =a work colleague; and 5 =a stranger with a good business idea. The year in which respondents were interviewed: To facilitate a more intuitive interpretation of estimated coefficients than would be the case if the actual year of survey (e.g., 2001, 2002, 2003) were used, we constructed a rescaled measure by subtracting 2000 from the year of the survey (i.e., 2001 respondents received a code of “1,” 2002 respondents received a code of “2,” and 2003 respondents received a code of “3”). Respondent's age in years Respondent's sex (1 = male; 2 = female) Four dichotomous variables indicating the highest educational degree attained by the respondent (“No education”, “Some secondary education”, “Secondary degree”, “Post secondary education”, and “Graduate degree”): the “Secondary degree” category as the reference category Respondent’s occupational status (1 = “Full or part time work”; 0 = “Not working” or “Retired or student”) Three dichotomous variables (the upper, middle or lower third of the income distribution of the country of origin): the middle income group as the reference category Respondents were asked whether they knew personally someone who had started a business in the two years preceding the survey (0 =No; 1=Yes) Respondents were asked whether they believed to have the knowledge, skill, and experience required to start a new business (0=No; 1=Yes) Respondents were asked whether fear of failure would prevent them from starting a business (0 = No; 1 = Yes)

GEM GEM

GEM

GEM GEM GEM

GEM GEM GEM GEM GEM

Country-level variables Generalized trust

Breadth of formal organization memberships ln(GDP) GDP growth Diversity Availability of institutional loans

Dummies for legal origin % of Protestants

The percentage of individuals in each country who believe that others can be trusted (from the following question: “Generally speaking, would you say that most people can be trusted or that you need to be very careful in dealing with people?”) The average number of different types of formal organization memberships (e.g., in religious organizations, social welfare services, education, arts, music or cultural activities, trade unions, environmental groups, and professional associations) of individuals in a country The natural log of Gross Domestic Product (GDP) per capita (constant 2000 US$) from the previous year of the survey GDP per capita growth from the previous year of the survey to the year of the survey (annual %) The average value of ethnic fractionalization and cultural diversity scores (alpha = 0.88) The average of responses to the following items: “It is possible to obtain a loan with only a good business plan and no collateral,” “Venture capital is readily available for new business and development,” and “During the past year, credit has become easier to obtain.” The three-item measure was internally consistent (Cronbach's alpha: 0.82). The items had 7 response options, from 1 (strongly disagree) to 7 (strongly agree). In order to capture the effect of legal institutions, Djankov et al.'s (2003) classification of countries according to legal tradition was used, omitting English-law countries for ease of interpretation The percent of the population for Protestants in a country

WVS

WVS

World Development Indicators (WDI) Online World Development Indicators (WDI) Online Fearon (2003) World Economic Forum (2000)

Djankov et al. (2003) Fox (2006)

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