of the four labor supply outcomes. However, the other personality traits did not enter significantly. When using the structural latent model approach, the stability aggregated measure (Alpha, a composite of agreeableness, conscientiousness, and emotional stability) positively and significantly affects hourly wages while plasticity (beta, a composite of openness to experience and extroversion) affects the probability of employment. Grit increases the likelihood of being wage worker or white‐collar.

The difference in the results derived from the OLS and a structural model with latent skills suggest measurement bias in the non‐cognitive skills used in this analysis. While plasticity was not correlated with any labor force outcomes estimated through OLS, the results from the structural latent variable model shows that plasticity is positively correlated (at the 5% level) with being employed, suggesting that the OLS methodology underestimates the role of plasticity in employment outcomes. In contrast, OLS predicts a correlation between grit and four of our five outcomes while the structural latent skills model only finds a correlation between grit and two job‐ quality outcomes (wage worker and white collar). This suggests that OLS overestimates the role of grit in wage and employment outcomes. Finally, while stability is only correlated with wages in both methodologies, the estimated coefficient emerging from the OLS is negative while a positive coefficient estimate emerges from the structural latent variable model. This suggests that OLS severely underestimates the role of stability (kindness, cooperation, emotional stability, conscientiousness) on wages.

The different results emerging from the OLS and the structural latent variable estimation points to the need for better data to determine which non‐cognitive skills are appropriate for developing country economies. The data used in this paper provide the minimum number of variables necessary to construct latent variables to proxy non‐cognitive skills that are generally accepted by the profession (aggregating non‐cognitive to just three measures). But these skills – stability, plasticity, and grit – are too aggregated to be policy relevant. Future work will require the survey teams to define _ex ante_ the skills that they wish to correlate with labor market outcomes and design surveys such that a minimum of three measures can be used to construct the latent variables in the structural methodology. Further, since non‐cognitive skills develop over time, and current labor status is a result of choices and actions taken in the past, panel data are needed to provide more robust results.

While Peruvian schools already teach cognitive skills, these findings suggest that the Peruvian government is well justified in incorporating non‐cognitive skill development into the school curriculum. Although the non‐cognitive skills explored in this paper only encompass personality traits, which are commonly assumed to not be malleable to interventions, emerging research is finding that, indeed, interventions do have short‐run effects on personality (Magidson et al. 2014; Jackson et al. 2012). However, there is a significant body of research that quantifies the positive impact of program interventions on specific behaviors that can be linked to the personality traits explored in this paper.<sup>38</sup>

> 38 These program designs are varied and too numerous to present here, but Guerra, Modecki, and Cunningham (2014) provides such a mapping and links to the mapping a list of programs with empirical evidence that show a positive impact of these behaviors in various countries throughout the world.

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