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Estimating the critical and sensitive periods of investment in early childhood: A methodological note

Listed author(s):
  • Popli, Gurleen
  • Gladwell, Daniel
  • Tsuchiya, Aki

The identification of critical periods in early human development requires statistical analyses beyond simple cross tabulation of correlations of observed variables. This paper provides an overview of different quantitative methods available for the statistical analysis of longitudinal data regarding child development, and in particular the identification of critical and sensitive periods for later abilities. It draws heavily on the work on human skill formation developed by the economist James Heckman, which treats ability as a latent variable and explains its formation through the simultaneous estimation of structural equations of investments and achieved abilities across time. We distinguish between two specifications of the ability formation function. One of them (the ‘recursive’) format explains current ability as a function of the ability and investment at the immediately preceding period. The other (the ‘non-recursive’) format explains current ability as a function of a series of past investments. In order to fully examine critical and sensitive periods of investments, the non-recursive formulation needs to be used. Furthermore, true abilities of an individual cannot be directly observed: what we observe are the test scores, for example, on reading and writing. We outline an approach, structural equation modelling, that treats actual test scores as measurements of the latent ability variable, and show how it can be used in the recursive and non-recursive formulation. In order to fully examine critical and sensitive periods of investments, we argue that the non-recursive formulation of this structural model is necessary. However, the non-recursive formulation requires more data than the recursive formulation, and to the best of our knowledge, has never been used in the identification of critical and sensitive periods in early childhood development.

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Article provided by Elsevier in its journal Social Science & Medicine.

Volume (Year): 97 (2013)
Issue (Month): C ()
Pages: 316-324

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Handle: RePEc:eee:socmed:v:97:y:2013:i:c:p:316-324
DOI: 10.1016/j.socscimed.2013.03.015
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  1. Portrait, France & Teeuwiszen, Erica & Deeg, Dorly, 2011. "Early life undernutrition and chronic diseases at older ages: The effects of the Dutch famine on cardiovascular diseases and diabetes," Social Science & Medicine, Elsevier, vol. 73(5), pages 711-718, September.
  2. Petra E. Todd & Kenneth I. Wolpin, 2007. "The Production of Cognitive Achievement in Children: Home, School, and Racial Test Score Gaps," Journal of Human Capital, University of Chicago Press, vol. 1(1), pages 91-136.
  3. 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).
  4. Currie, Janet & Thomas, Duncan, 1995. "Does Head Start Make a Difference?," American Economic Review, American Economic Association, vol. 85(3), pages 341-364, June.
  5. Carneiro, Pedro & Heckman, James J., 2003. "Human Capital Policy," IZA Discussion Papers 821, Institute for the Study of Labor (IZA).
  6. Gabriella Conti & James Heckman & Sergio Urzua, 2010. "The Education-Health Gradient," American Economic Review, American Economic Association, vol. 100(2), pages 234-238, May.
  7. 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, May.
  8. Petra E. Todd & Kenneth I. Wolpin, 2003. "On The Specification and Estimation of The Production Function for Cognitive Achievement," Economic Journal, Royal Economic Society, vol. 113(485), pages 3-33, February.
  9. Elwell-Sutton, Timothy M. & Jiang, Chao Qiang & Zhang, Wei Sen & Cheng, Kar Keung & Lam, Tai Hing & Leung, Gabriel M. & Schooling, C.M., 2011. "Socioeconomic influences at different life stages on health in Guangzhou, China," Social Science & Medicine, Elsevier, vol. 72(11), pages 1884-1892, June.
  10. Eric I. Knudsen & James J. Heckman & Judy L. Cameron & Jack P. Shonkoff, 2006. "Economic, Neurobiological and Behavioral Perspectives on Building America's Future Workforce," NBER Working Papers 12298, National Bureau of Economic Research, Inc.
  11. Eric A. Hanushek, 1998. "Conclusions and controversies about the effectiveness of school resources," Economic Policy Review, Federal Reserve Bank of New York, issue Mar, pages 11-27.
  12. Flavio Cunha & James J. HECKMAN, 2009. "Investing in our Young People," Rivista Internazionale di Scienze Sociali, Vita e Pensiero, Pubblicazioni dell'Universita' Cattolica del Sacro Cuore, vol. 117(3), pages 387-418.
  13. Eric A. Hanushek, 2003. "The Failure of Input-Based Schooling Policies," Economic Journal, Royal Economic Society, vol. 113(485), pages 64-98, February.
  14. Eric Knudsen & James J. Heckman & Judy Cameron & Jack P. Shonkoff, 2006. "Economic, Neurobiological and Behavioral Perspectives on Building America’s Future Workforce," World Economics, World Economics, 1 Ivory Square, Plantation Wharf, London, United Kingdom, SW11 3UE, vol. 7(3), pages 17-41, July.
  15. Sanchez, Brisa N. & Budtz-Jorgensen, Esben & Ryan, Louise M. & Hu, Howard, 2005. "Structural Equation Models: A Review With Applications to Environmental Epidemiology," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 1443-1455, December.
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