To explore the importance of families for society, we investigate how parental mental health affects the ASB of adolescents. It is also important to explore this issue to contribute to a large literature exploring how the characteristics of parents affect the characteristics of their children, (see Dohmen et al., 2011; Chevalier et al., 2013). To explore the effects of parental mental health on adolescent’s ASB, we estimate the effects of the mother's and father's GHQ(36) score on the four measures of ASB using Sample 1. Badly behaved adolescents may have an adverse effect on the mental health of their parents thus leading to reverse causality. To mitigate this issue, we measure the mental health of parents in wave 1 or wave 2 of Understanding Society prior to the measurement of ASB.82
Table 3.9(a) presents the coefficients from estimating equation (A3.1), which is presented in Appendix 2. As demonstrated in panel (1), there is no statistically significant effect of paternal mental health on the participation of adolescents in the four ASBs.
However, the findings contained in panel (2) suggest that poorer maternal mental health is positively associated with fighting, shoplifting, and truancy behaviours. The effect of maternal mental health on truancy behaviour is statistically significant at the 10%, but not the 5%, level. There is no statistically significant effect of maternal mental health on vandalising behaviour. The marginal effects revealed in Table 3.9(b) suggest that a one standard deviation (5.21) increase in maternal mental health problems predicts a 1.46% point increase in the probability that adolescents participate in fighting. The effect of a one standard deviation increase in maternal mental health problems on fighting is approximately 20% of the size a one standard deviation increase in the overall mental health problems of the adolescent.
82 We measure the mental health of parents using the first available measure of the GHQ(12) in wave 1 or wave 2 of Understanding Society. For approximately two thirds of adolescents we measure the mental health of parents in wave 1 and for a third of adolescents we measure the mental health of parents in wave 2. To explore the effects of parental mental health on adolescent's ASB we estimate equations (A3.1) outlined in Appendix 1.
99 One mechanism via which the mental health of mothers may affect the ASB of adolescents is via its indirect effect on the mental health of adolescents. To explore this possibility, the empirical specifications presented in Table 3.9(a) were re-estimated controlling for the contemporaneous mental health of the adolescent. In the models relating to fighting and truancy, after conditioning upon the mental health of the child, the coefficient of the maternal mental health variable shrinks in magnitude by approximately 50-60% and becomes statistically insignificant. In contrast, for the shoplifting variable, after controlling for the mental health of the adolescent, the coefficient of the maternal mental health variable becomes approximately 30% smaller but remains statistically significant at the 10%, but not the 5%, significance level83. In contrast, after controlling for the mental health of the adolescent, the effect of maternal mental health on vandalism increase in magnitude by approximately 300% and becomes statistically significant at the 5% level. This is a surprising finding for which there is no obvious explanation. Hence, these findings therefore support the case that one important pathway via which the mental health of mothers may affect the fighting, shoplifting, and truancy behaviours of adolescents is via the indirect effect of parental mental health on adolescent mental health.
The empirical results presented in Table 3.9(a) support the case that the mental health problems of mothers may have a larger effect on the ASB of adolescents, relative to the effects of the mental health problems of fathers. There are a number of explanations for this finding. Firstly, data from the UK Harmonised European Time Use Survey from 2015 suggests that, on average, fathers spend approximately 1.9 hours per week on childcare, 2.6 fewer hours per week than that spent by mothers, see Office for National Statistics (2016d). As a result, one explanation for the differences in the effects of the mental health of mothers and fathers on the ASB of adolescents is that mothers spend more time with their children, and therefore the mental health of mothers may have a greater effect on adolescent ASB than that of fathers.
Secondly, arguably, children may have a stronger bond with their mother than their father and hence the mental health of mothers may have a greater effect on the ASB of their child. For example, Lundberg et al. (1997) show that child benefits provided to the mother lead to a higher expenditure on the child than providing the income to the father, holding total family income constant. This finding supports the notion that mothers may have a stronger preference for the welfare of their children than fathers84. In addition, previous evidence indicates that young children typically turn to their mothers preferentially at times of feeling distressed, see Lamb (2010). One interpretation of these findings is that the mother-child bond may be stronger than the
83 These results are available upon request. 84
Additional evidence from evolutionary biology suggests that parental differences in altruism may result from differences in biology such as women possessing a larger gamete, internal fertilisation inside the mother, and lactation. For an interesting overview of how evolutionary biology may lead to differences in parental altruism written for an economist audience, see Alger and Cox (2013).
100 father-child bond and hence the mental health of mothers may have a more prominent effect on the ASB of adolescents than that of fathers.
3.6 Robustness Check 1: Multivariate Probit Models
To test the robustness of the findings revealed in Tables 3.7(a) to 3.8(b), we explore the effects of adolescent's mental health on their participation in ASB using multivariate probit models. Table 3.10 reveals selected coefficients from the multivariate probit models and the full estimation results are provided in Table A3.1 in Appendix 3. In common with our main findings shown in Tables 3.7(a) to 3.8(b) we utilise Sample 1. The evidence illustrated in column (1) of Table 3.10 suggests that poorer overall mental health of adolescents is positively associated with the probability that they participate in fighting, vandalism, shoplifting, and truancy.
The results contained in column (2) illustrate the relative effects of externalising problems and internalising problems on adolescent's participation in ASB. For each of the 4 indicators of ASB, the effect of externalising problems remains statistically significant at the 1% level. In addition, the effect of internalising problems on fighting behaviour remains statistically significant at the 10% level, in accordance with the estimates found in Table 3.7(a). In contrast to the findings presented in Table 3.8(a), the effect of internalising problems on truancy behaviour is borderline statistically significant (P-value = 0.053). In common with our previous findings, there is no statistically significant effect of the tendency to internalise on vandalising and shoplifting behaviours, as can be seen in column (2). Furthermore, note the standard errors in the joint modelling approach (presented in Table 3.10) are smaller relative to standard errors of the single-equation models. It is therefore evident that the joint modelling approach is more efficient.
For the measures of fighting, vandalism, and truancy, the coefficients of the mental health variables in the multivariate probit models are approximately 80% of the magnitude of the coefficients of the single-equation models (see Table 3.7(a) and 3.8(a)). In contrast, for the measure of shoplifting, the coefficients of the measures of mental health in the multivariate probit models are approximately 60% of the magnitude of those presented for the single-equation models. Shoplifting is the least prevalent ASB: approximately 2% of adolescents reported to participate in the past year (see Table 3.1). Consequently, the effects of adolescent mental health on participation in shoplifting may be more sensitive to the choice of model, relative to the more prevalent ASBs (fighting, vandalism, and truancy).
The rho parameter estimates at the bottom of Table 3.10 show the estimated correlations between the cross-equation error terms of the 4 ASB models (see Section 3.4.2 for further details). Note that each of the 6 rho parameters are positive and statistically significant, thus suggesting that the 4 ASB models are related via their error terms. The largest estimated correlation in the error terms is between the
101 shoplifting and vandalism equations (0.47 and 0.41 in models (1) and (2), respectively). In contrast, the smallest correlation between the cross-equation error terms is between the shoplifting and fighting equations and is 0.24 and 0.18 in models (1) and (2), respectively. This suggests that unobserved characteristics that affect participation in shoplifting may have a larger effect on vandalism relative to their effect on fighting behaviour.
Also, the chi-squared test statistics for the likelihood ratio test of the multivariate probit model relative to the single-equation framework are greater than 110 for both models. As a consequence, we reject the null hypothesis of the independence of the error terms (i.e. 𝜌𝐹𝑉 = 𝜌𝐹𝑆 = 𝜌𝐹𝑇 = 𝜌𝑆𝑉 = 𝜌𝑇𝑉 = 𝜌𝑇𝑆 = 0) thus endorsing the joint
modelling approach.
3.7 Robustness Check 2: Conditional Logit Models
The findings of Sections 3.5.1 and 3.6 support the case that adolescents who have a greater tendency to externalise are more likely to engage in ASB. As an additional robustness check, we estimate conditional logit models to explore the effects of the mental health of adolescents on their ASB using family fixed effects. The coefficients from the conditional logit models are shown in Table 3.11. We estimate the conditional logit models using Samples 4(a) to 4(c), for further details see Section 3.4.3.
The empirical analysis displayed in column (1) suggests that poorer overall mental health is positively associated with participation in fighting. This effect remains statistically significant at the 1% level. Additionally, the evidence revealed by column (2) suggests that greater externalising problems are positively associated with the probability of fighting. However, the coefficient of the internalising problems variable on fighting is statistically insignificant, but changes little in magnitude relative to the findings shown in Tables 3.7(a) and 3.10. This may be a result of the lower power of these smaller samples to detect an effect.
The evidence provided in column (3) suggests that poorer overall mental health of adolescents has a positive and statistically significant effect on the probability of participating in vandalism. The final column of Table 3.11 reveals that an increased tendency to externalise is associated with a higher probability of vandalism. This coefficient is statistically significant at the 1% level. In common with our previous findings, there is no statistically significant effect of the tendency to internalise on the probability that an adolescent participates in vandalism. The results also indicate that fighting is more common amongst males, younger adolescents, and adolescents who stay out late, and that males more commonly participate in vandalism.
In accordance with the previous results, the conditional logit estimates displayed in column (1) of Table 3.12 suggest that poorer overall mental health is associated with a
102 greater probability of engaging in truancy. Additionally, the effect of externalising problems on truancy remains positive and statistically significant at the 1% level, but there is no statistically significant effect of internalising problems on truancy. Column (2) suggests that females are more likely to participate in truancy than males. In accordance with our previous findings, truancy is more common amongst older adolescents. Finally, adolescents who stayed out late three or more times in the past week have a greater probability of engaging in truancy, relative to adolescents who never stayed out late in the past week.
The conditional logit estimation results shown in Tables 3.11 to 3.12 suggest that the propensity of adolescents to externalise is positively associated with the probability of fighting, vandalism, and truancy, and hence support the robustness of our previous findings.
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