|Equation||(# participants) x (% counterfactual rate of service) x (% increase in annual earnings) x (Effectiveness of program) x ($ average annual earnings for high school graduates) x (# working years)|
|Explanation||This metric estimates the impact of programs that improve non-cognitive skills for youth on lifetime earnings. Non-cognitive skills include intra- and inter-personal competencies in human development related to personality, emotions, and social skills. These may include self-esteem, locus of control, and motivation, etc. Most programs focused on these types of skills also impact academic, mental health, and substance abuse outcomes. We determine all these potential outcomes and the availability of data to estimate them during the assessment process. We then apply trumping rules to avoid double counting.
Number of participants who receive services: Reported by program.
Counterfactual rate of non-cognitive services for youth: Determined by Constellation staff based on a landscape analysis of the program.
Increase in annual earnings: [0.03]. This is the average increase in annual earnings for black and Latino youth per standard deviation change in self-esteem, locus of control, or motivation towards academic goals. This is estimated using summary data from Jones et al. (2015). For programs serving Latina females, we use [0.09].
Effectiveness of program: Estimated standard deviation using program data on pre-post assessments or the percent of participants who successfully complete the program.
Average annual earnings for high school graduates: [$24,700]. This is estimated using ACS data (U.S. Census Bureau, 2016).
Number of working years: Estimate from participation age to age 65.
These benefits are then discounted to present value.
|References||Jones, D. E., Karoly, L. A., Max Crowley, D., & Greenberg, M. T. (2015). Considering Valuation of Noncognitive Skills in Benefit-Cost Analysis of Programs for Children. Journal of Benefit-Cost Analysis, 6(3), 471–507.
U.S. Census Bureau. (2016). American Community Survey 5-year estimates – public use microdata sample, 2012-2016. Generated using Public Use Microdata Area (PUMA) in the Seven-county Twin Cities Metropolitan Area.