Statistical modeling
cognitive and socio-emotional skills
(1) Educational outcomes: We expected the entrepreneurship program to affect certain educational outcomes, such as registration to the university selection test (i.e., Prueba de Selección Universitaria, PSU) and high school dropout. Both outcomes could be thought as proxies of positive aspirations or motivation. Administrative data on educational outcomes are only accessible at the end of each academic year. We estimate a simple Probit model comparing treatment and control groups at the end of the year, which can be written as:(2) Emotional regulation: A key contribution of this study is the use of a novel methodology, EEG recordings paired with the James-Lange theory of valence and arousalWe estimate a difference-in-difference model given by:Additionally, we estimate the net effect of entrepreneurship on emotion responsiveness (i.e., valence and arousal) by measuring the difference of changes of emotion respect to negative/positive stimuli, which can be summarized by:With the difference-in-difference model and measurement of net effect, we can control for all time-invariant characteristics within and between groups. By subtracting the average differences between groups before the program started and only comparing the difference after the program, we can account for any pre-existing differences between the groups. This methodology also helps to control for any other unobserved variables that may affect both groups in a similar way.(3) Socio-emotional Skills, Creativity, and Cognitive Skills: The entrepreneurship program was expected to positively impact the socio-emotional skills of its participants. Using conventional self-reported tests, we measured grit (perseverance) and locus of control. Additionally, the program was expected to impact creative and innovative skills, which are a mixture of both cognitive and socio-emotional skills. Note that the literature demonstrating best practices for measuring creativity remains scarce, particularly in the context of educational program evaluationsIn this specification, In order to achieve the highest possible statistical power in these estimations, we used both non-treated 12th grade (