The neglected role of formal and informal institutions in women’s entrepreneurship: a multi-level analysis

Institutions are “the rules of the game” of a society that function as constraints and define human interactions (North 1990). Institutions are classified into formal institutions—such as constitutions, laws and property rights—and informal institutions derived from culture (North 1990). Formal and informal institutions are intertwined, and interactions between them establish an equilibrium in the economy (Aoki 2001). Thus, the rules of the game define the institutional evolution of an economy and the way entrepreneurs are constrained, enabled and guided by the institutional framework in which they are embedded (Nooteboom 2002). Although North (1990) considers entrepreneurs in general (e.g., social entrepreneurs, economic entrepreneurs, etc.), in this article, we refer to entrepreneurs as individuals who have established businesses. According to Williamson (2000), institutional theory proposes the concept of the “embeddedness” of informal institutions in society, in which culture plays a large role. The nature of informal institutions is abstract, and they mostly go unnoticed (Helmke and Levitsky 2004). However, they interact with formal institutions and affect individual behaviors (North 1990). We therefore suggest that institutional theory may shed light on the “hidden” institutions that may amplify or mitigate the effect of informal institutions on women entrepreneurs (Brush et al. 2009).

Individual characteristics and attributes may influence the likelihood that women will become entrepreneurs (e.g., Langowitz and Minniti 2007; McGowan et al. 2012) and that institutions play a crucial role (e.g., Baughn et al. 2006). Several authors have suggested that women’s entrepreneurship has a multi-level nature (Elam and Terjesen 2010; Terjesen et al. 2013). Brush et al. (2009) propose a holistic framework that is gender aware and goes a step beyond the market by including motherhood and meso- and macro-environmental factors. In this context, it is important to understand the way in which institutions (e.g., public policies and culture) influence women’s entrepreneurship because these institutions cannot be easily changed and are difficult to control (Brush et al. 2009). In recent years, an effort has been made to understand the influence of formal institutions on the likelihood that women will become entrepreneurs (Thébaud 2016). For example, Goltz et al. (2015) observe that interactions of different public policies (e.g., gender quotas within parliaments, the rule of law, etc.) positively affect women’s likelihood of becoming entrepreneurs. However, recent studies have also attempted to understand the effects of informal institutions on women’s entrepreneurship (e.g., Baughn et al. 2006). Baughn et al. (2006) show that culture affects the proportion of women and men entrepreneurs differently; in particular, societies that have strong entrepreneurial cultures have higher proportions of women entrepreneurs. In sum, the results of these studies suggest that formal and informal institutions help explain the observed gender differences in the likelihood of becoming entrepreneurs across countries (Elam and Terjesen 2010; Estrin and Mickiewicz 2011) and the gender gap in entrepreneurial activity globally (Thébaud 2015).

According to some scholars, the interaction between formal and informal institutions (Helmke and Levitsky 2004; North 1990) affects entrepreneurial behavior (Giménez and Calabrò 2018; Tonoyan et al. 2010). We examine how the interaction between informal and formal institutions influences the likelihood that women will become entrepreneurs. Our research model is shown in Fig. 1.

North (1990, p. 73) argues that the interaction of formal and informal institutions (among other factors, such as technology and income) determines “the potential wealth-maximization opportunities of entrepreneurs.” Based on this idea, scholars have found that the interaction between formal and informal institutions has an effect on individual behaviors, particularly on entrepreneurial behaviors. However, this effect has not been properly investigated in women’s entrepreneurship research. Research on women’s entrepreneurship has focused on examining the differential effects of institutions on men and women entrepreneurs (Estrin and Mickiewicz 2011; Thébaud 2015) as well as understanding how formal institutions influence women entrepreneurs (e.g., Goltz et al. 2015). These studies show the complex interaction between formal and informal institutions and how they determine women and men’s economic behaviors (North 1990). Little is known about how the interaction between formal and informal institutions affects women entrepreneurs. Therefore, in this article, instead of distinguishing between the influence of formal and informal institutions, we examine the interactions between them by examining how informal institutions (masculinity, power distance, individualism, and indulgence) moderate the effects of formal institutions on the likelihood that women will become entrepreneurs. We argue that masculinity, power distance, individualism, and indulgence moderate this relationship because informal institutions may influence women entrepreneurs more than formal institutions do (Alvarez and Urbano 2011; Noguera et al. 2013). Therefore, informal institutions, particularly those related to gender norms, are strong determinants of women’s engagement in economic activities, especially becoming entrepreneurs (Klyver et al. 2013).

We use Hofstede’s conceptualization of culture¹ (masculinity, power distance, individualism and indulgence), which has been used extensively in the entrepreneurship literature to understand the role of culture in entrepreneurship (e.g., Mitchell et al. 2000). Hofstede (2001) defines culture as the “collective programming of the mind that distinguishes the members of one group or category of people from another.” Therefore, Hofstede’s culture dimensions capture the informal institutions suggested by North. North (1990) suggests that culture is a common set of values, which gives a language-based conceptual framework for encoding and interpreting information on this set of values and knowledge. Culture is taken for granted and is not subjected to scrutiny or judgment (Jepperson 1991). Therefore, culture becomes part of the mindset and affects individual behaviors. Hofstede’s definition of culture is closely connected to informal institutions. We believe that culture could show us a comprehensive overview of how the values of different societies provide an answer to why women participation in entrepreneurship is generally low and varies greatly worldwide. Indeed, investigating cultural dimensions as informal institutions could reveal some gendered components at the society level and the way that societies perceive entrepreneurship (Bruton et al. 2010).

Individual and macro-level data were gathered from multiple sources. Individual-level data, such as our dependent variable, were collected through the Adult Population Survey (APS) conducted by the GEM. The GEM APS collected data from approximately 2000 adults (aged 18 to 64) in each country. The data were collected through telephone or face-to-face interviews. This survey has been used in various comparative studies (De Clercq et al. 2013), supporting the notion that it provides reliable and valid data (Reynolds et al. 2005; Thébaud 2015), especially for the use of multi-level modeling techniques. The process of merging the data was as follows. We used the data from the GEM, which collects data in 60 countries. The GEM teams collected data from individuals in different countries; in each country, the data collected varies from 500 to 13,000 individuals. In 2010, the GEM project collected from 176,684 participants, of which 85,560 were male and 91,124 were female. Since our aim is to understand the effect of family policies as formal institutions and cultural dimensions as informal institutions, we needed to merge the data with the OECD data, the Hofstede data and the World Bank Group. We used the OECD data for obtaining family policy information. Due to the limited number of countries that participate in the OECD, the data reduce from 60 countries to 21 countries. Then, we included Hofstede’s data, which were collected from 101 countries and included more than 50 questions for capturing the cultural dimensions (Hofstede et al. 2010). We merged the data with Hofstede cultural dimensions, representing those countries that needed to match the countries from the OECD data. While merging the datasets, we observed that only one country did not have information on Hofstede cultural dimensions; thus, we had a sample of 20 countries. We also used data from the World Bank Group for controlling at the country level, again necessitating a match with the countries in the sample. In sum, we excluded observations with missing data and observations from countries where information on public policies and cultural dimensions are not available from the OECD family dataset, the World Bank or Hofstede’s culture dimensions. Therefore, our final sample is 27,200 women from 20 countries (Australia, Belgium, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Japan, Korea, Mexico, the Netherlands, Norway, Portugal, Spain, Sweden, the UK, and the USA).

Our dependent variable is a dummy variable (the likelihood that women will become entrepreneurs). Thus, we use a hierarchical linear modeling (HLM) approach: logistic regression with random effects. This technique allows us to analyze the relationship between the predictor variable and a binary outcome in the case of non-independent outcomes (Hox et al. 2010). This technique assumes that unobserved country-specific characteristics (u0j), which are randomly distributed with mean zero, constant variance and uncorrelated predictors, covary. Thus, this technique allows us to observe that the constant term varies randomly among countries (Autio et al. 2013). HLM has several advantages over conventional regressions because discounting the interdependency between the individual and the country level can lead to inaccurate estimates (Hofmann 1997). The observations within groups (e.g., countries) are correlated and not independently distributed (Aguinis et al. 2013; Hox et al. 2010). Thus, multi-level analysis is an appropriate technique for analyzing our theoretical model. To facilitate the interpretation, all predictor variables are z-standardized (Autio et al. 2013; Stephan et al. 2015).

As previously mentioned, in the first step of the hierarchical analysis, we include only the dependent and control variables (individual and country level) (model 1). In the second step, we add the control and independent variables (country level) (model 2). Finally, we add the (country level) predictor and moderator variables in models 3, 4, 5, 6, and 7. All models are estimated using STATA 13.0.

To test the robustness of our results, we conducted additional analyses. We used a different measurement of the dependent variable: likelihood of men becoming entrepreneurs (“1”). In these analyses, the final sample consisted of 27,231 individuals from 20 countries. We analyzed the correlation matrix, and, again, we observe that uncertainty avoidance and the long-term dimensions were highly correlated to the independent variables. The findings indicate that the women and men’s samples differ. The relationship between the public expenditure on childcare and the likelihood that women will become entrepreneurs was negative and significant, while the length of parental leave was positively and significantly associated with the likelihood of men becoming entrepreneurs. When we introduced the interaction terms, the findings suggest, on the one hand, that the interaction between power distance and the public expenditure on childcare was negative and statistically significant and, on the other hand, that the length of parental leave was positive and statistically significant. Moreover, the interaction between masculinity and the public expenditure on childcare was not significant. The interaction between masculinity and the length of parental leave was negative and significant. Then, the interaction term of individualism and the public expenditure on childcare was not significant, but the length of parental leave is negative and significant. Finally, the interaction between indulgence and the public expenditure on childcare did not have a statistically significant on the likelihood that men will become entrepreneurs. However, the interaction between indulgence and the length of parental leave was statistically significant and positive. Therefore, we observe that the main effect and the interaction terms influence women and men’s likelihood of becoming entrepreneurs differently. Hence, formal and informal institutions have a differential effect on men and women entrepreneurs.

Moreover, using the Global Leadership & Organizational Behavior Effectiveness (GLOBE) data, we reran our analyses. We first ran a correlation matrix and observed that institutional collectivism, uncertainty avoidance and the long-term dimensions had a high correlation with the public expenditure on childcare and the length of parental leave. Therefore, we did not include these dimensions in our analyses. Thus, we used human orientation, future orientation, gender egalitarianism, in-group collectivism, and performance orientation. The results have some similarities and differences to our results when we used the Hofstede dimensions. Similar to the results from the Hofstede dimensions, the GLOBE project results show that the interaction between the family policies and the power distance dimension did not have a significant effect on the likelihood that a woman will become entrepreneur. When we tested human orientation, we observed that the interaction between the family policies and the human orientation dimension does not influence women’s likelihood of becoming entrepreneurs. However, the future orientation dimension shows different results: we observed that future orientation reduces significantly the effect of public childcare on the likelihood that women will become entrepreneurs. Moreover, future orientation amplifies the negative effect of the length of parental leave and women’s likelihood of becoming entrepreneurs. Interestingly, gender egalitarianism and in-group collectivism did not have a significant effect on the relationship between the family policies and the likelihood that women will become entrepreneurs. Instead, performance orientation shows different results: the interaction between the public expenditure on childcare and performance orientation did not have a significant effect on women’s likelihood of becoming entrepreneurs. However, the interaction between the length of parental leave and performance orientation was positive and statistically significant. These results show that the interaction between formal and informal institutions occurs when using different datasets. Additionally, the results give a robustness to our theoretical model and show how cultural dimensions increase or reduce the effect of the public expenditure on childcare and the length of parental leave on women’s decision to start new ventures.

Building on arguments from institutional theory, as theorized by North (1990), we hypothesized that formal institutions, which differ across countries and are represented by family policies such as the public expenditure on childcare and the length of parental leave, have significant effects on the likelihood that women will become entrepreneurs. Furthermore, we hypothesized that informal institutions—such as power distance, masculinity, individualism, and indulgence—moderate the relationship between formal institutions and women’s likelihood of starting ventures.

The results from our study point to the important contribution of the public expenditure on childcare to the likelihood of women becoming entrepreneurs. In the context of new institutional theory in which formal institutions shape individual behaviors (North 1990), women’s likelihood of becoming entrepreneurs is related to the role of formal institutions that cannot be easily changed and are difficult to control (Brush et al. 2009). Formal institutions such as family policies that aim at increasing the participation of women in the labor market also affect women’s decisions to become entrepreneurs. Therefore, as our findings show, the public expenditure on childcare in a country strongly reduces a woman’s desire to become entrepreneur.

However, in keeping with new institutional economics, institutions shape the likelihood of women becoming entrepreneurs. As institutions are created to reduce uncertainty (North 1990), the effect of formal institutions varies between women and men’s decisions, in particular the decision to become entrepreneurs. Given the benefit for working parents to participate in the labor market, we expected a reduction of the likelihood that women will become entrepreneurs when parental leave is longer, as women prefer to be employed. However, our findings suggest that the length of parental leave does not have a significant effect on women entrepreneurs. This finding suggests the complexity of the institutional context surrounding women entrepreneurs (Brush et al. 2009).

Previous findings provide mixed results on the public expenditure on childcare and the length of parental leave (Estrin and Mickiewicz 2011; Thébaud 2015), suggesting the complex institutional context that women face when deciding to become entrepreneurs and the benefits that the labor market provides. Literature on women’s entrepreneurship supports this perspective (Klyver et al. 2013), arguing that to increase the participation of women in entrepreneurship, public policies should be aligned and balanced with respect to entrepreneurship as well as the labor market (Ahl and Nelson 2010).

The findings suggest that high masculinity and individualism moderate the impact of the public expenditure on childcare on women’s likelihood of becoming entrepreneurs. To better interpret these findings, we plot the significant interactions in Figs. 2, 3, and 4 (p < 0.05).

We observe that this effect occurs in countries characterized by medium and high levels of masculinity, such as the USA, Greece, France, and Japan. As shown in Fig. 2, the likelihood of a woman becoming an entrepreneur decreases when the public expenditure is high on childcare and with medium/high masculinity. These results are in line with the previous literatures, which show a negative relationship between the public expenditure on childcare and the likelihood of women becoming entrepreneurs (e.g., Estrin and Mickiewicz 2011; Thébaud 2015). By contrast, we observe that in highly masculine countries, women entrepreneurs may perceive the benefits of the public expenditure on childcare, namely, public childcare facilities. These facilities help reduce the number of hours that women spend taking care of their children, but these benefits are mainly in the labor market. The public expenditure on childcare seems to strengthen traditional gender roles in the society because women would prefer to work in the labor market, leading to fewer women becoming entrepreneurs.

We plotted the significant interaction between individualism and public expenditure on childcare (see Fig. 3). The plot shows that, in low-individualistic countries, a higher public expenditure on childcare positively affects the likelihood of women becoming entrepreneurs. This effect only occurs in countries with low individualism (e.g., Greece, Korea, and Mexico). A possible explanation is that low-individualistic countries maintain traditional gender roles in society (Parboteeah et al. 2008); thus, family relations are more important than business ones. However, in high-individualistic societies, the public expenditure on childcare does not have a significant effect because gender equality may be embedded at the society and women levels; therefore, women perceive that they have the same opportunities as men do (Fletcher 2006). Consequently, the impact of the public expenditure on childcare is not significant on women entrepreneurs in these types of societies.

Further, we plotted the significant interaction between indulgence and the length of parental leave (see Fig. 4). The plot shows that when indulgence increases, the length of parental leave increases the likelihood that women will become entrepreneurs. An explanation is that women are highly empowered in high-indulgent societies because having a long length of parental leave in a country may be perceived as a supportive state to employees as well as to entrepreneurs. Consequently, entrepreneurship seems a great opportunity for creating new ventures (Buttner and Moore 1997) because people are empowered and perceive they have the support of states. Entrepreneurship thus provides a way to decrease gender inequality (Bird and Brush 2002). Conversely, in a low-indulgent society, entrepreneurship may be perceived as an unconventional way to earn money (Baughn et al. 2006). For this reason, women would prefer to enter the labor market due to the security that labor markets provide. Therefore, the likelihood that a woman will become an entrepreneur decreases.

In our robustness checks, we ran our model on a sample of men to determine whether there were differences in becoming entrepreneurs and on GLOBE data to observe whether the interactions are significant using different cultural measures. Again, we found support that the interaction between formal and informal institutions influences men’s likelihood to become entrepreneurs but in a different way than it does for women. For example, in the men-only sample, the interaction between power distance and family policies is significant, but in the women-only sample, it was not. Another example is that the interaction between masculinity and the length of parental leave is significant for the men-only sample, while in the women-only sample, this interaction is not significant, but the interaction between masculinity and the public expenditure on childcare is. These results highlight the role played by formal and informal institutions and give strong support to our arguments that institutions shape men and women entrepreneurial behaviors differently. This finding also suggests that the recent conversation in the entrepreneurship literature around the importance of the institutional context (Welter 2011) has a gendered component of cultural dimensions. Additionally, using GLOBE data provides a stronger support to our findings. Our robustness checks indicate that different cultural variables influence the relationship between formal institutions and women entrepreneurs, supporting the gendered component of culture. These results show that women are significantly sensitive to the institutional context (Welter 2011).

This study first contributes to the field of entrepreneurship (Autio et al. 2013; Thébaud 2015) because we could observe that the interactions of formal and informal institutions affect women’s likelihood of becoming entrepreneurs. Through our robustness checks, we also observed that men’s likelihood of becoming entrepreneurs is influenced by the interactions of formal and informal institutions; however, these effects differ between women and men samples. Our findings extend the literature of institutions and entrepreneurship in that we go deeper than testing the direct effect and find that their interactions play a key role in becoming entrepreneurs. Thus, we contribute to the literature that investigates entrepreneurship and institutions through a multi-level approach (De Clercq et al. 2013; Schölin et al. 2017; Stephan et al. 2015), in particular, by investigating the role that culture as an informal institution plays in entrepreneurship (Bruton et al. 2008; Engelen et al. 2009; Oo et al. 2018). Second, our findings extend the literature of women’s entrepreneurship because we can observe the effect of the institutional context on their likelihood of becoming entrepreneurs. Even though the current literature has advanced on the reasons women are less likely than men to become entrepreneurs (e.g., Baughn et al. 2006; Estrin and Mickiewicz 2011), these studies have tested separately whether some formal or informal institutions influence them. Instead, in our study, we could observe the complex and important role that the interactions of public policies (formal institutions) and culture (informal institutions) have in women’s likelihood of becoming entrepreneurs. We could see that family policies on their own have a significant effect but this effect is moderated to a great extent by informal institutions such as masculinity, individualism and indulgence. Third, we address the call for more comparative research in the women’s entrepreneurship field by advancing both a macro-perspective (Autio et al. 2013; Yousafzai et al. 2015) and an examination of the variance in women’s entrepreneurship across countries (Verheul et al. 2006). This study supports the notion that women’s entrepreneurship has a multi-level nature (Elam and Terjesen 2010). Our findings suggest that women’s behaviors such as becoming an entrepreneur are better explained when the institutional context is properly considered (Giménez and Calabrò 2018; Welter 2011). We thus advance the reasons why women’s participation in entrepreneurship varies globally.

Based on our findings, we suggest to policymakers, who wish to increase the number of women entrepreneurs, to consider informal institutions when creating public policies. Since the effect of formal institutions, such as the public expenditure on childcare and the length of parental leave, varies across countries, particularly if the countries are characterized by high levels of masculinity, individualism and indulgence. Therefore, policy makers should analyze the cultural context and design public policy to be effective in a specific country. We also consider that public policies, which promote women’s entrepreneurship, should be designed from a long-term perspective to reduce the effect of informal constraints in the future (e.g., masculinity, individualism, and indulgence) (Helmke and Levitsky 2004). Finally, we suggest that these policies should be continuously revised to assess their effectiveness.

Several limitations of this study should be noted. First, due to missing data, the sample size in our study was 20 countries. Future research should include developed, transitioning and developing economies, thus allowing for the observation of entrepreneurial dynamics in different countries and, possibly, different clusters. Second, although multi-level techniques are useful for considering different levels of analysis, we could use data only from 2010. Future research should increase the number of years used to examine patterns over time. Moreover, following Helmke and Levitsky (2004)’s typology of informal institutions, such as complementary and accommodating institutions, further studies could more deeply examine how the interaction between formal and informal institutions influences women’s entrepreneurship. Third, by collecting data from mum-entrepreneurs, we could investigate the way that being a mom influences women either to become entrepreneurs or their growth aspirations. Fourth, although we compared women entrepreneurs and non-entrepreneurs, we suggest an examination of women’s transitions from the labor market to entrepreneurship and of the formal and informal institutions that may influence this decision. Fifth, it would be interesting to study the nexus of institutions, women entrepreneurs and economic growth, considering female entrepreneurship as a mediator between the institutional context and economic performance (Aparicio et al. 2016). Finally, it would be interesting to examine further how institutional conditions affect women’s motivation to become entrepreneurs to understand whether this motivation is driven by opportunity, necessity or purpose (pursuing social or sustainable ventures).