Forecasting and Mediation
There is a substantial body of evidence showing that early childhood programs can boost the skills of disadvantaged children. Most of this research has evaluated the short-run ‘treatment effects’ of these programs, focusing on outcomes such as cognitive test scores, school readiness, and measures of social behavior. So far, few studies have analyzed longer-term effects such as completed education, adult health, crime, and labor income.
Heckman and Garcia (2020) aimed to bridge this gap in research, focusing on influential early childhood programs for disadvantaged children in North Carolina. Guided by economic theory, the study shows that it is possible to supplement experimental data with non-experimental data to ‘forecast’ the life-cycle benefits and costs of the programs.
These predictions combine microsimulation using non-experimental data with experimental data from the midlife follow-up study.
The figure below shows the contributions to the present value of major program components. The high rate of return and benefit-cost ratio that we find has multiple sources. Our analysis is a template for estimating the life-cycle gains of social experiments for which there is less than full lifetime follow-up. Supplementing experimental data with non-experimental data enhances the information available from social experiments. Using economic theory and econometric methods to generate empirically concordant forecasts enhances the credibility of our procedure.