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Understanding the Mechanisms through Which an Influential Early Childhood Program Boosted Adult Outcomes

Author Info

Listed author(s):
  • James Heckman
  • Rodrigo Pinto
  • Peter Savelyev

Abstract

A growing literature establishes that high quality early childhood interventions targeted toward disadvantaged children have substantial impacts on later life outcomes. Little is known about the mechanisms producing these impacts. This paper uses longitudinal data on cognitive and personality skills from an experimental evaluation of the influential Perry Preschool program to analyze the channels through which the program boosted both male and female participant outcomes. Experimentally induced changes in personality skills explain a sizable portion of adult treatment effects.

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Article provided by American Economic Association in its journal American Economic Review.

Volume (Year): 103 (2013)
Issue (Month): 6 (October)
Pages: 2052-2086

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Handle: RePEc:aea:aecrev:v:103:y:2013:i:6:p:2052-86
Note: DOI: 10.1257/aer.103.6.2052
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Find related papers by JEL classification:
  • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
  • I24 - Health, Education, and Welfare - - Education - - - Education and Inequality
  • I28 - Health, Education, and Welfare - - Education - - - Government Policy
  • J13 - Labor and Demographic Economics - - Demographic Economics - - - Fertility; Family Planning; Child Care; Children; Youth
  • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

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  1. James Heckman & Seong Hyeok Moon & Rodrigo Pinto & Peter Savelyev & Adam Yavitz, 2010. "Analyzing social experiments as implemented: A reexamination of the evidence from the HighScope Perry Preschool Program," Quantitative Economics, Econometric Society, vol. 1(1), pages 1-46, 07.
  2. Flavio Cunha & James J. Heckman & Susanne M. Schennach, 2010. "Estimating the Technology of Cognitive and Noncognitive Skill Formation," Econometrica, Econometric Society, vol. 78(3), pages 883-931, 05.
  3. James Heckman, 2011. "Policies to foster human capital," Educational Studies, Higher School of Economics, issue 3, pages 73-137.
  4. Heckman, James J. & Kautz, Tim, 2012. "Hard evidence on soft skills," Labour Economics, Elsevier, vol. 19(4), pages 451-464.
  5. Borghans Lex & Golsteyn Bart H.H. & Heckman James & Humphries John Eric, 2011. "Identification Problems in Personality Psychology," Research Memorandum 025, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
  6. R. Jennrich & P. Sampson, 1966. "Rotation for simple loadings," Psychometrika, Springer;The Psychometric Society, vol. 31(3), pages 313-323, September.
  7. Heckman, James J. & Moon, Seong Hyeok & Pinto, Rodrigo & Savelyev, Peter A. & Yavitz, Adam, 2010. "The rate of return to the HighScope Perry Preschool Program," Journal of Public Economics, Elsevier, vol. 94(1-2), pages 114-128, February.
  8. Clive R Belfield & Milagros Nores & Steve Barnett & Lawrence Schweinhart, 2006. "The High/Scope Perry Preschool Program: Cost–Benefit Analysis Using Data from the Age-40 Followup," Journal of Human Resources, University of Wisconsin Press, vol. 41(1).
  9. Almlund, Mathilde & Duckworth, Angela Lee & Heckman, James & Kautz, Tim, 2011. "Personality Psychology and Economics," Handbook of the Economics of Education, Elsevier.
  10. John Carroll, 1953. "An analytical solution for approximating simple structure in factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 18(1), pages 23-38, March.
  11. Charles Crawford & George Ferguson, 1970. "A general rotation criterion and its use in orthogonal rotation," Psychometrika, Springer;The Psychometric Society, vol. 35(3), pages 321-332, September.
  12. Bolck, Annabel & Croon, Marcel & Hagenaars, Jacques, 2004. "Estimating Latent Structure Models with Categorical Variables: One-Step Versus Three-Step Estimators," Political Analysis, Cambridge University Press, vol. 12(01), pages 3-27, December.
  13. Anderson, Michael L., 2008. "Multiple Inference and Gender Differences in the Effects of Early Intervention: A Reevaluation of the Abecedarian, Perry Preschool, and Early Training Projects," Journal of the American Statistical Association, American Statistical Association, vol. 103(484), pages 1481-1495.
  14. John Horn, 1965. "A rationale and test for the number of factors in factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 30(2), pages 179-185, June.
  15. Robert Jennrich, 2006. "Rotation to Simple Loadings Using Component Loss Functions: The Oblique Case," Psychometrika, Springer;The Psychometric Society, vol. 71(1), pages 173-191, March.
  16. Flavio Cunha & James J. Heckman, 2008. "Formulating, Identifying and Estimating the Technology of Cognitive and Noncognitive Skill Formation," Journal of Human Resources, University of Wisconsin Press, vol. 43(4).
  17. Louis Guttman, 1954. "Some necessary conditions for common-factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 19(2), pages 149-161, June.
  18. Joseph P. Romano & Michael Wolf, 2005. "Exact and Approximate Stepdown Methods for Multiple Hypothesis Testing," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 94-108, March.
  19. Alexei Onatski, 2009. "Testing Hypotheses About the Number of Factors in Large Factor Models," Econometrica, Econometric Society, vol. 77(5), pages 1447-1479, 09.
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