6.4 Socioemotional Skills Differ between the Top and Bottom Wealth Quintiles

FIGURE 6.4 Socioemotional Skills Differ between the Top and Bottom Wealth Quintiles

Source: Estimates based on data of the 2014 Pakistan lSS and 2012 Sri lanka STEP. Note: Only statistically significant results are reported.

create a selection bias given that there are many possible reasons that the value of the wages of other respondents may be missing and that it is theoretically likely that unobservable or unmeasured factors may affect both the wages and the probability of observing a wage. The Heckman selection model is used to correct for this bias by first identifying variables that affect the probability of observing wages—not the actual wages—and then estimating the prospective wages without selection bias. The selection variable in this model is the probability that workers will have an observed wage, while the outcome variable is observed wages. However, the ordinary least squares regression model based on the Mincer equation is used for Sri Lanka because the Wald test of independent errors from selection and outcome equations is not rejected, that is, error terms from selection and outcome equations are not correlated. Thus, the nonselection hazard measured by the inverse Mills ratio will have no impact on the outcome, conditional on the observation of the wage, thereby making the use of the Heckman selection equation on the data unjustified.

There may be measurement bias in most socioemotional skill indicators because these indicators are self-reported. In Peru, Cunningham, Parra Torrado, and Sarzosa (2016) find differing results in the ordinary least squares and the structural model. They conclude that there is a strong measurement bias in most socioemotional skills measures in the data used. Their paper illustrates the significant impacts of socioemotional skills on labor market outcomes, although the patterns are nonuniform by methodology and labor market outcome. For example, the perseverance of effort (grit) was strong in most outcomes regardless of methodology. However, plasticity—a composite of openness to experience and emotional stability—was only correlated with employment and only if the structural latent model was used.

In Pakistan, the returns to socioemotional skills are mostly statistically insignificant, except for agreeableness (figure 6.5). After controlling for cognitive skills (measured by Raven scores), educational attainment, parental education, wealth, work experience, nature of the employment, access to finance, and location, only the impact of agreeableness remains statistically significant. However, it is associated with negative returns to earnings. The impact of agreeableness on earnings may vary by culture. For instance, Lee and Ohtake (2016) find that Japanese men who reported a higher level of agreeableness earned more, whereas American men with a higher level of agreeableness experienced a penalty. However, in both countries, agreeableness had a positive impact on earnings among individuals working in companies with more than 1,000 employees. This finding also suggests that agreeableness improves job performance and productivity directly, rather than indirectly through occupational choice. Because the majority of the jobs in Pakistan are created by small and medium enterprises, it is possible that personality traits linked with competitiveness may be valued more than agreeableness. However, the penalty is relatively small: with every unit increase in agreeableness, the monthly wage declines by only 0.3 units.

In Sri Lanka, socioemotional skills are not significantly related to earnings in the informal sector (figure 6.6). However, in the formal sector, emotional