In this section, we investigate the transmission of risk attitudes between generations and whether it is gendered. To do this, we start by examining the intergenerational transmission of attitudes. We also examine positive assortative mating and the transmission of attitudes from the local environment.
Transmission from parents to children
Previous research has indicated that willingness to take risk is correlated across domains, in which taking risk in general could be a proxy for other risk domains (e.g., Dohmen et al. 2011). However, with the recent integration of individual-difference psychology into economics (e.g., Almlund et al. 2011; Borghans et al. 2008), risk attitudes could arguably be domain specific (Weber et al. 2002) and gendered. Therefore, we would conduct our analysis with the general self-reported risk question and deepen our analysis by checking our results for risk attitudes in traffic and financial matters.
We begin our analysis by looking at Fig. 2, which gives us a first glimpse of the pattern in willingness to take risk in general between parents and children. Figure 2 shows children’s average willingness to take risk in three domains (illustrated in Panels A to C) for each given scale (from 1 to 10) of their parents self-reported risk attitudes. The regression lines in Fig. 2 are based on a weighted regression of children’s general risk attitudes on their mother’s and father’s general risk attitudes.Footnote 6
Figure 2 indicates, in line with Dohmen et al. (2012), a positive relationship between children’s willingness to take risk and their mother’s or father’s willingness to take risk in general. However, extending the findings of Dohmen et al. (2012) that concentrate only on the general risk domain, the same positive relationship is also seen for risk taking in traffic and financial matters.Footnote 7
The average age of children in the sample is 24.4 years (SD 6.27). The oldest child is 56 years old. Half of the children in the sample are older than 22 years old. The average age of mothers is 49.8 (SD 8.97) and fathers 60.6 years old (SD 10.75).
Table 1 shows children’s willingness to take risk in general as the dependent variable regressed on the main explanatory variables being children’s mother’s and father’s willingness to take risk in general, while controlling for several confounding factors.Footnote 8 For a detailed overview of the control variables used in this study, see Sepahvand and Shahbazian (2017). The same procedure has been performed for risk taking in traffic and in financial matters.Footnote 9
Starting with risk attitudes in general, as shown in Table 1, M1 indicates that on average children show a higher willingness to take risk in general as their parents’ willingness to take risk in general increases. The coefficient estimates for mother’s and father’s willingness to take risk are significant and have the same sign as previous research (Dohmen et al. 2012), indicating that children’s risk attitudes are correlated with parents’ attitudes. However, compared to the findings of Dohmen et al. (2012), who show that the coefficients for the mother and the father are both of comparable size, the magnitude of our coefficient is different for mothers and fathers. This provides an initial indication that a heterogeneity might exist in terms of gender in the intergenerational correlation between parents and children. This is an issue that we analyze in detail in the section about gender differences below.
M2 and M3 in Table 1 include additional control variables, such as sex and age as controls, which previous research has shown to have a significant association with risk attitudes in Burkina Faso. We see that the positive relationship between children’s and mother’s and father’s willingness to take risk continues to stay intact and significant.Footnote 10
To see whether the intergenerational correlation in risk attitudes is robust, an identical re-estimation of risk attitudes in general is conducted, with the sole difference being that the main explanatory variables are willingness to take risk in traffic and financial matters. Table 1 shows that the coefficient estimates for mother’s and father’s risk attitudes are significant for the domains of risk taking in traffic and financial matters. Thus, the estimates show that the results remain robust. However, there is a heterogeneity in risk attitudes across domains. For instance, the strong association detected from mothers’ risk attitudes on children’s willingness to take risk in general is reversed for risk taking in traffic. Instead, in Table 1, we see that fathers seem to have a stronger effect than mothers on children’s willingness to take risk in traffic.
Heterogeneity in risk attitudes across domains
The results so far have indicated a heterogeneity in risk attitudes across domains. It could be that risk attitudes in one domain (such as financial) predict risk attitudes in other domains (such as traffic). If that were the case, it would be quite damaging to the interpretation of our results as this could be an indication that the transmission of attitudes, within domains, is rather unspecific and vague; taking risk in a particular domain is explained equally well by risk attitudes in that domain or any other domain. If, on the other hand, the domain-specific measure captures distinct attitudes toward risk, we would see that risk measurement in the corresponding domain has the greatest explanatory power. Consequently, it is necessary to conduct a detailed analysis of whether parents’ risk attitudes in all three domains can predict the children’s risk attitude in a specific risk domain. In Table 2, children’s willingness to take risk in one particular domain has been regressed on parents’ willingness to take risk in all domains simultaneously.Footnote 11
Table 2 indicates a positive and significant diagonal pattern of estimated coefficients, in line with previous literature (Dohmen et al. 2012). This implies that when we control for risk attitudes in all domains, children’s risk attitudes in a given domain have a higher association and is more significant with those of their parents risk attitudes in the same domain. Moreover, the pattern shown in Table 2 is a further evidence of similarity across generations and risk domains.
Positive assortative mating
According to Bisin and Verdier (2000), one mechanism behind the socialization from parents to their children is positive assortative mating. However, theoretically assortative mating could be either positive or negative (Lam 1988). For instance, assuming that the family is a provider of the production of a joint utility, the couple could optimize its utility in certain production decisions by being diversified in its risk attitudes, such as one being a risk lover and the other more averse (Chiappori and Reny 2006). Hence, there could be an urge for negative assortative mating by the couples. Consequently, whether there is a negative or positive assortative mating between couple becomes an empirical question.
Table 3 shows the results for the transmission of risk attitudes between spouses.Footnote 12 The dependent variable is the female partner (mother’s) risk attitudes. The results show that there is a strong positive association between the male partner (fathers) risk attitudes and their spouses’ risk attitudes (mothers). The coefficient estimates are robust across model specifications, as shown from M1–M3 in Table 3. This is an indication of positive assortative mating along the dimension of risk taking, i.e., individuals are paired with other individuals that have similar attitudes. It is important to note, extending the findings of Dohmen et al. (2012) who only investigate one risk domain as shown in Table 3, that the same strong and positive effect in traffic and financial matters is found, i.e., the effect is not domain driven.
Homogeneous and heterogeneous risk attitudes
To deepen our analysis about positive assortative mating and the transmission of attitudes further, we return to our initial estimations from Table 1 but now with the focus on mothers with homogeneous attitudes compared to single mothers, which are more frequent in Burkina Faso than single fathers. If positive assortative mating is in line with the theory of attitude transmission, then those mothers who have similar or homogeneous attitudes as their partners should have a stronger influence on their child’s attitudes (i.e., direct transmission of attitudes) compared to single mothers. According to the theory of attitude transmission, it is assumed that single or divorced parents are less effective in socializing the child than homogeneous parents (Bisin and Verdier 2000). This is another reason as to why individuals tend to seek a partner with similar attitudes, i.e., positive assortative mating.
In Table 4, we estimate the relationship between the child and mother’s risk attitudes for those children who live with a single mother and those who live with a mother living together with a spouse with homogeneous attitudes. Our coefficient estimates are in line with the theory. We see that single mother’s influence on their child’s risk attitudes is less than those mothers living with a spouse with similar risk attitudes. For instance, mothers living with a partner who has homogeneous attitudes, as indicated by M2 in Table 4, have a stronger association on their child’s risk attitudes in general compared to single mothers in M1. This effect is consistent across domains for traffic and financial matters. Dohmen et al. (2012) find the reverse effect, more in line with the idea that children with single mothers are influenced somewhat to the same degree as children with mothers in homogeneous parent couples. Their finding could be contextual. In a German context, if there is no optimal match of partner, the institutional setting allows the single mother to have a stronger influence on the child as a role model, as she can choose not to match with a randomly chosen individual and thus continue to be a single parent.Footnote 13 However, this does not hold for developing countries such as Burkina Faso with weak underdeveloped institutions and strong gender roles. Societal norms make it more difficult to be a single parent.Footnote 14
Transmission from local environment to children
The previous results above indicate a strong positive impact of intergenerational transmission of attitudes, i.e., parents’ risk attitudes influence child’s risk attitudes. However, other individuals could be in the surrounding environment who influence the child’s risk attitudes, such as local role models as stated by oblique transmission of attitudes between generations, mediating the direct transmission from parents to children.
Regional risk attitudes
Table 5 shows the step-wise results for including parents’ risk attitudes (M1), the average regional risk attitude (M2), and additional control variables (M3).Footnote 15 Starting with risk attitudes in general, the regional willingness to take risk has a positive and significant associative effect on child’s general risk taking. In line with Dohmen et al. (2012), average regional willingness to take risk does not mediate the influence of parents. However, when taking a closer look at our estimations, we see a difference across domains. For risk taking in general and traffic, the effect from regional attitudes is strong and positive, but never stronger in magnitude than the parental transmission of risk attitudes (except for mothers in traffic). However, for risk taking in financial matters, we see a stronger regional associative effect on the child’s risk attitudes, which is stronger than their parents’.
We concluded that our results are consistent with the theory of transmission of attitudes that a channel of transmission of attitudes exists from the local environment on the child’s attitudes. Moreover, our coefficient estimation from M3 indicates that the local environment risk attitudes are in line with previous research. For instance, we see that estimations on mother’s and father’s willingness to take risk are robust across model specifications in Table 5, i.e., they do not fundamentally change when including regional attitudes. This is also consistent with our results from Table 1 M3 and with previous literature (Dohmen et al. 2012), showing that when controlling for region, it does not affect the intergenerational transmission of attitudes between parents and children.Footnote 16
As discussed earlier, in Burkina Faso, traffic is more male dominated, while the daily financial transactions are female dominated. Thereby, the fact that different risk domains are gendered is likely to affect the transmission of attitudes between generations.
As a first step, in order to detect any gender difference across domains, we turn to the results in Table 1, in which a clear shift is seen when it comes to parents’ influence on their child’s risk attitudes between risk taking in traffic and financial matters. Table 1 shows that the association between fathers and their children in traffic is stronger than the association between mothers and their children. The opposite is evident for risk taking in financial matters; the association between mothers and children is stronger than that between fathers and children. Since risk domains are gendered, the socialization of daughters and sons might also be gendered.
Table 6 divides the sample by child’s gender and re-estimates the same regressions as shown in Table 1. Table 6 shows a strong gender difference between mother’s and father’s depending on whether the child is a girl or boy. Mothers have a stronger associative influence on their daughter’s willingness to take risk, independent of domain. For instance, daughters are more associatively influenced by their mother’s willingness to take risk in general compared to their fathers. Furthermore, mothers also associatively have a lesser influence on their sons’ risk taking in general compared to their spouses. Focusing on fathers, Table 6 shows that they affect their son’s risk taking more when compared to their wives. Also, fathers associatively influence their daughters risk taking less compared to their spouses. These patterns are indications that strong gender roles exist in terms of transmission of risk attitudes between generations. To ensure that these patterns are not reflected by issues related to our relatively smaller sample size for daughters (564) compared to sons (1556), we compare, as sensitivity tests, the mean value of risk attitudes for daughters and other female non-relatives in the same household. The average risk attitudes for daughters (female non-relatives) are 3.9 (4.0) for risk taking in general, 3.4 (3.3) for risk taking in traffic, and 4.3 (4.2) for risk in financial matters. As another sensitivity test, we compare the mean value of women in our analytical sample to all other women that have answered our risk-attitude questions. The difference between the analytical sample women (other women) is 3.7 (3.6), 2.9 (2.7), and 4.3 (4.2) for risk taking in general, traffic, and financial matters. We see the same pattern but with higher mean values when doing the same comparison for men. When comparing the mean value for risk attitudes of unmarried daughters and sons living in the same household, we get a correlation of 0.97. These tests give us an indication that the daughters in our sample are not a selective group.
The results in Table 6 also indicate that different risk domains are gendered, extending the results of Dohmen et al. (2012) that do not find any such effects in Germany. In the male-dominated risk domain (traffic), the transmission of risk attitudes from fathers to daughters is relatively stronger than in the female-dominated risk domain (financial matters), while the transmission of risk attitudes from mothers to sons is relatively stronger in the female-dominated risk domain (financial matters) than in the male-dominated risk domain (traffic). This gender heterogeneity in risk domains implies that the parents in the domain that they are more exposed to socialize children more in that setting.