The traditional economic approach to youth risk taking is, as mentioned, a utility maximization/opportunity-cost approach. Forward-looking individuals pursue a certain activity if the expected benefits of it exceeds the expected costs. One example of model using this approach is the “Theory of Rational Addiction” (TORA) developed by Becker and Murphy (1988). According to the TORA, the utility of an individual depends on the consumption of two goods, c and y. The difference between the two goods is that while the utility generated by the current consumption of y is completely independent of past choices, the present utility derived by the consumption of c depends on the past consumption of c. This is what characterize habits or addiction. In other words, the TORA assumes that instantaneous utility depends on current consumption of the addictive good, the stock of past consumption of the addictive good, and current consumption of all other goods.
Developmental psychology, although not necessarily in contrast to the traditional economic approach, considers a wider variety of factors determining youth decisions to engage in risky behaviours. As Fischhoff (1992) effectively summarizes, according to developmental psychologists, (risk) decision-making depends on three groups of factors: how people ‘think’ about the world, i.e. their capacity for thinking through problems, examining the alternative available and evaluating their implications (‘cognitive’ development); how people ‘feel’ about the world (‘affective’ development) and the roles that others play in people’s choices (‘social’ development).
In this paper we conceptually integrate the psychology component into a more general economic model of decision making taking the inspiration from behavioural economics (O’Donoghue and Rabin 2001) and the economic literature on skills formation (Cunha and Heckman 2007).
As argued by Borghans et al. (2008a), preferences are central to conventional economic choice models. Agents decide in a decision horizon T the bundle of good to consume based on their preferences and constraints (typically, information constraints and budget constraints). They also acknowledged the role of dynamic constraints connected to asset, skills and traits formation. Their model is consistent with a framework were individual preferences change over time, individual decisions are time inconsistent and discount rates as well as preferences may vary with ‘age, mood, personality traits and cognition’. They argue that cognitive and personality traits can affect consumption choices through different mechanisms including risk aversion, inter-temporal preferences and the valuation of leisure.
Insights from behavioural economics are hugely important to understand why young people might behave differently than adults. Empirical evidence suggests that young people are excessively myopic with respect to the future and therefore are more likely to have inconsistent preferences over time (Gruber and Koszegi 2001; O’Donoghue and Rabin 2001). More specifically, they have the tendency to have a higher discount rate in the short run than in the long run. Young people respond to the uncertainty about the future by reducing the importance of the future, an effect known as hyperbolic discounting. Furthermore, they tend to under-appreciate the effect of changes in their states and the extent to which their preferences may adapt over time. Because of that, they tend to inappropriately project the current preferences onto their future tastes (projection bias) (Loewenstein et al. 2003; O’Donoghue and Rabin 2001). For this reason, random changes to their current states affect their long-run decision making. Also, youth tend to be less risk averse which is consistent with the myopia and hyperbolic discounting features (Gruber and Koszegi 2001; O’Donoghue and Rabin 2001). Moreover, risky decisions are made in uncertain environments and for many risky activities, the cost is one-time and permanent. Uncertainty and one-time cost with longer term implications might increase risk-taking behaviours and a mistake made in the past becomes permanent in its consequences. Finally, younger teens tend to be both more impatient and subject to peer pressure (Lewis 1981).
All these characteristics might help in explaining why risky behaviours are more prevalent among young people. On the other side, there are at least three factors which might counterbalance this: biology, income and law (Gruber 2001). Indeed, some risky activities (e.g. sexual intercourse) become desirable with age (biology). Moreover, some illegal activities for younger teens become legal at older ages (e.g. cigarettes consumption is illegal to under 19 in Peru) (law). Finally, older teens may have more money available to finance their risky activities (income).
2.1 Psychosocial competencies and cognitive skills as predictors of risky behaviours: evidence from policy and research
Many studies in the economic literature find evidence of contemporaneous correlation between different risky behaviours (Chaloupka and Laixuthai 1997; Dee 1999; DiNardo and Lemieux 2001; DuRant et al. 1999; Farrelly et al. 2001; Model 1993; Wiefferink et al. 2006). Those evidence support the ‘bad seed’ hypothesis, as described by Gruber (2001). The hypothesis is that there is a certain segment of the youth population that is predisposed towards risky activities, while others are not. In that case, policies targeting the segment of population at risk should work effectively. An alternative hypothesis in psychological literature is that there is a certain amount of risk that youths have the tendency to take (‘conservation of risk’ hypothesis). Reducing risky activity in one area would have a substitution effect by increasing risky activities in another. To date, most intervention programmes have been targeting specific groups of the population considered at risk, mainly by targeting single risk behaviours. Most recently, there are examples of interventions taking a broader approach and target more than one risky behaviour at time. More specifically, they aim to address some underlying determinants of risky behaviours which are believed to protect young people from, or predispose them to, distinct risky behaviours. Therefore, a better understanding of which childhood traits predict risky behaviours is crucial from a policy perspective.
Empirical evidence suggest that interventions focusing on improving cognitive skills or aimed at improving soft skills are effective in reducing risky behaviours. An example of an intervention aimed at improving opportunities for children coming from poor backgrounds is the well-known Perry Preschool Programme, an intervention targeting a sample of 3–4-year-old African–American children living in poverty and assessed to be at high risk of school failure. Although the literature originally focused on the cognitive impact of the intervention, long-term effects have in fact been more persistent in non-cognitive areas. Heckman et al. (2010) and Conti et al. (2015) show that Perry significantly enhanced adult outcomes including education, employment, earnings, marriage, participation in healthy behaviours, and reduced participation in crime teen pregnancy, and welfare dependency later in life. Interestingly, although the programme initially boosted the IQs of participants, this effect soon faded. A persistent effect of the programme has been found on improvements in personality skills (e.g. it reduces aggressive, antisocial, and rule-breaking behaviours). On the other side, Hill et al. (2011) show that several interventions that focus on personality rather than only on cognitive skills were effective at reducing delinquency and traits related to delinquency.
Few economic papers analyse the role of personality traits and non-cognitive skills on criminal activities, or more generally, risky behaviours. Heckman et al. (2006) find that self-esteem and locus of control measured during adolescence are as powerful as cognitive abilities in predicting adult earnings. Moreover, they find that personality factors for men affect the probability of daily smoking more than cognitive factors and the opposite is true for women. Similarly, Cunha et al. (2010) show that personality traits are relatively more important in predicting criminal activity than cognitive traits are. Further, Conti and Heckman (2010) suggest that personality and health status measured during adolescence explain more than 50% of the difference in poor health, depression and obesity at age 30. For males, personality traits and health endowments are more predictive than cognitive skills while for women they are equally predictive.
The role of self-efficacy and self-esteem as predictors of risky behaviours has been discussed in the psychological literature, particularly its role during the adolescence period. This is because during this stage individuals commonly start experimenting with risky activities (including alcohol abuse, smoking, drug use, and unprotected sex). Bandura et al. (2001) state that perceived self-efficacy (in the areas of academic, social, and self-regulatory efficacy) is important to resist peer pressure for transgressive activities, a view also shared by other authors (e.g. Wills 1994). Empirical evidence shows a negative relationship between self-efficacy and risky or delinquent behaviours, including use of alcohol and drugs, physical and verbal aggression, theft, cheating and lying (Bandura et al. 2001; Bandura et al. 2003). In addition, self-efficacy is thought to be important to change unhealthy behaviours, such as smoking (Schwarzer 2001).
In the case of self-esteem, a negative relationship with risky behaviours is expected (Donnellan et al. 2005). First, people with low self-esteem perceive that they have less social ties (Rosenberg 1965), which in turn decrease conformity to social norms and increase delinquency. Second, it is theorized that aggression and antisocial behaviour are motivated by feelings of inferiority rooted in early childhood experiences. In addition, it is thought that self-esteem mediates the impact of stress, which is of a subjective nature (Baumeister et al. 2003). People with high self-esteem are likely to experience less stress because they interpret negative events more benignly, are more optimistic about their coping abilities, and perceive they have more control compared to people with low self-esteem.
Notwithstanding these arguments, others have argued that a positive relationship could arise, as noted by Baumeister et al. (2003). While it is true that young people with low self-esteem might be more prone to engage in risky behaviours—for solace when they feel bad about themselves, young people with arguably high self-esteem might have biases in their interpretation of events that allow them to feel better about themselves, either by minimizing their own vulnerability or by distorting how their parent will react. This is likely to be the case in particular for people with unrealistically high self-esteem, close to narcissism (Donnellan et al. 2005).
Baumeister et al. (2003) provide a review of the literature about the role of self-esteem on several life outcomes, including smoking, alcohol and drug abuse, and unprotected sex. They conclude that evidence linking low self-esteem to risky behaviours during the adolescence is mixed and inconclusive, with positive, negative and zero effects found, particularly in the case of alcohol use, whereas in the case of smoking, the relation is mainly negative. On the other hand, Donnellan et al. (2005) use data from three different datasets which strongly support the notion that low self-esteem is related to aggressive behaviour.
An important aspect is whether self-esteem and self-efficacy can be measuring similar dimensions of a person self-concept. In fact, some authors (Dercon and Krishnan 2009; Epstein et al. 2004) suggest that self-efficacy can be treated as a determinant of self-esteem. Wills (1994) shows empirical evidence that supports the notion that self-efficacy might be a more important factor than self-esteem, and suggests that, in absence of a control for self-efficacy, previous studies might have overstated the importance of self-esteem. Overall, what this seems to suggest is that it is important to control for both psychosocial dimensions in order to estimate the individual contribution of each.
At the heart of the traditional opportunity cost approach to risky behaviours and of intertemporal choice models described above, are individual expectations. As mentioned, people make decisions taking into account the present utility, their expectations about future utility. Present-biased time preferences are likely to be more frequent among people who are pessimistic about their future. Consistently with the ‘opportunity cost’ argument in the risky behaviour literature, if an outcome is perceived as inaccessible, people might believe that they have little to lose by engaging in risky behaviours. There is a considerable body of economic literature investigating the role of aspirations and subjective expectations for contraceptive choices (Delavande 2008), (sexual) risky behaviour (De Paula et al. 2013; Shapira 2013) and non-marital childbearing choices (Wolfe et al. 2007). As Dalton et al. (2016) argue, how far people aspire depends on their own beliefs about what they can achieve with effort, i.e. their own expectations. People would not aspire to an outcome that is perceived as inaccessible. However, given the endogenous nature of aspirations, the empirical distinction between aspirations and expectations is hard to achieve in a non-experimental setting and often aspirations are used interchangeably with expectations.
Finally, the decision making model described above, yields several important implications regarding the role that cognition plays for the probability to engage in risky behaviours. There are a number of mechanisms through with cognitive skills might affect individual decision making, some of which can be amplified by the interaction between cognitive skills and schooling. First, individuals with higher cognitive skills might be more able to access information and more efficient at interpreting it. Second, cognitive skills are likely to shape preferences. As argued by Dohmen et al. (2010), people with better cognition appear to be more patient. They are also more willing to take risks. One potential explanation is that they are better able to envision future consequences and somehow reduce ambiguity about the future. In this sense, increased cognitive ability favourably influences behaviours, particularly when information is limited or idiosyncratic.
Schooling is also considered a protective factor against risky behaviours (see for example Cutler and Lleras-Muney 2010). First, education promotes the accumulation of both cognitive and socio-emotional skills, which affects the way individuals process information and behave. Second, education shapes the nature of the social network available to the individual, which can have either a positive or a negative effect (Behrman 2015; Peters et al. 2010). Third, education might shape time preferences, e.g. because schooling focuses students’ attention on the future (Becker and Mulligan 1997; Fuchs 1982). Fourth, people with more education might be better informed about negative health consequences, either because they learned about these consequences in school, or because better educated people find it easier to obtain and evaluate such information (De Walque 2007; Kenkel 1991). Fourth, education could also influence behavior by increasing the opportunity cost of engaging in risky behaviours, i.e. by increasing future income.
2.2 Other predictors of risky behaviours
The importance of family environment is well recognized by developmental research. Numerous studies show that children who grow up in single-parent families are more at risk of engaging in risky behaviours (see for example Evans et al. 1992). Adolescents from intact two-parent families tend delay the start of sexual activity relative to those in disrupted families (see for example Meschke and Silbereisen 1997). Clark and Loheac (2007) examine the consumption of tobacco, alcohol and marijuana in the USA and find that marijuana use is more widespread in single-parent families. They also find that smoking is more frequent amongst recent movers. Migration indeed might be potential source of instability. Gaviria and Raphael (2001) using secondary school data from the USA suggest that recent movers may be more susceptible to peer group pressure, at least with respect to the consumption of marijuana and cocaine.
Similarly, children who have older siblings have a higher probability of engaging in risky behaviours (Averett et al. 2011), and there might be a number of plausible explanations for that. It might be that older siblings affect their younger siblings’ behaviours indirectly, by being a role model to them and directly by proving them more opportunities to interact with a different group of older friends. An alternative explanation might be that parents spend less time in supervising their younger offspring (Aizer 2004).
It is worth to highlight that single parenthood as well as some other socio-economic characteristics frequently associated with poverty are some of the stronger predictors of risky behaviours. Risky sexual behaviours are often a manifestation of lack of opportunities, deprivation and poverty. Nevertheless, although risky behaviours are generally more prevalent in deprived socio-economic contexts, there is no consensus in the literature about the relative importance of different socio-economic indicators as independent determinants of adolescent risky behaviours. Some researchers have argued that parental educational attainment is a stronger predictor than other socio-economic indicators, such as household income or parental occupation (Goodman 1999).
Furthermore, it is not clear through which mechanisms the various indicators of socio-economic status might operate in affecting adolescents’ behaviours. Skills and competencies formation might be one of them. For example, it has been observed that scarce family resources are associated with low self-esteem (Amato and Ochiltree 1986) which in turn might be related with a higher risk of engaging in criminal and health-detrimental activities. Also, children who live in single-parent families show more behavioural problems and lower self-confidence (see for example Steinberg 1987).