1932

Abstract

This article reviews recent developments in the econometrics of early childhood human capital and investments. We start with a discussion about the lack of cardinality in test scores, the reasons it matters for empirical research on human capital, and the approaches researchers have used to address this problem. Next, we discuss how the literature has accounted for the errors in human capital measurements and investments. Then, we focus on the estimation of production functions of human capital. We present two different specifications of the production function and discuss when to use one versus the other. We describe how researchers have addressed cardinality, measurement errors, and endogeneity of inputs to estimate the technology of skill formation. Finally, we take stock of the work to date, and we identify opportunities for new research directions in this field.

Loading

Article metrics loading...

/content/journals/10.1146/annurev-economics-080217-053409
2021-08-05
2024-06-15
Loading full text...

Full text loading...

/deliver/fulltext/economics/13/1/annurev-economics-080217-053409.html?itemId=/content/journals/10.1146/annurev-economics-080217-053409&mimeType=html&fmt=ahah

Literature Cited

  1. Acemoglu D, Johnson S, Robinson JA 2001. The colonial origins of comparative development: an empirical investigation. Am. Econ. Rev. 91:51369–401
    [Google Scholar]
  2. Achenbach TM, Rescorla LA. 2001. Manual for the ASEBA school-age forms & profiles Rep., Res. Cent. Child. Youth Fam., Univ. Vt. Burlington:
    [Google Scholar]
  3. Agostinelli F, Wiswall M. 2016. Estimating the technology of children's skill formation NBER Work. Pap. 22442
    [Google Scholar]
  4. Aigner DJ, Hsiao C, Kapteyn A, Wansbeek T 1984. Latent variable models in econometrics. Handbook of Econometrics 2 Z Griliches, MD Intriligator 1321–93 Amsterdam: Elsevier
    [Google Scholar]
  5. Aizer A, Currie J, Simon P, Vivier P. 2018. Do low levels of blood lead reduce children's future test scores?. Am. Econ. J. Appl. Econ. 10:1307–41
    [Google Scholar]
  6. Aizer A, Eli S, Ferrie J, Lleras-Muney A. 2016. The long-run impact of cash transfers to poor families. Am. Econ. Rev. 106:4935–71
    [Google Scholar]
  7. Almlund M, Duckworth AL, Heckman J, Kautz T 2011. Personality psychology and economics. Handbook of the Economics of Education 4 E Hanushek, S Machin, L Woessmann 1–181 Amsterdam: Elsevier
    [Google Scholar]
  8. Almond D, Currie J, Duque V. 2018. Childhood circumstances and adult outcomes: act II. J. Econ. Lit. 56:41360–446
    [Google Scholar]
  9. Anderson TW, Rubin H. 1956. Statistical inference in factor analysis. Proceedings of the Third Berkeley Symposium on Mathematical Statistics and Probability 5 J Neyman 111–50 Berkeley: Univ. Calif. Press
    [Google Scholar]
  10. Aronson J. 2005. Biomarkers and surrogate endpoints. Br. J. Clin. Pharmacol. 59:5491–94
    [Google Scholar]
  11. Aslin RN. 2014. Phonetic category learning and its influence on speech production. Ecol. Psychol. 26:1–24–15
    [Google Scholar]
  12. Attanasio O, Cattan S, Fitzsimons E, Meghir C, Rubio-Codina M. 2020. Estimating the production function for human capital: results from a randomized control trial in Colombia. Am. Econ. Rev. 110:148–85
    [Google Scholar]
  13. Attanasio O, Cunha F, Jervis P 2019. Subjective parental beliefs: their measurement and role NBER Work. Pap. 26516
    [Google Scholar]
  14. Attanasio O, Fernandes C, Fitzsimons EOA, Grantham-McGregor SM, Meghir C, Rubio-Codina M. 2014. Using the infrastructure of a conditional cash transfer program to deliver a scalable integrated early child development program in Colombia: cluster randomized controlled trial. Br. Med. J. 349:g5785
    [Google Scholar]
  15. Barrett G, Donald S 2003. Consistent tests for stochastic dominance. Econometrica 71:71–104
    [Google Scholar]
  16. Bayley N. 1969. Bayley Scales of Infant Development San Antonio, TX: Psychol. Corp.
    [Google Scholar]
  17. Ben-Porath Y. 1967. The production of human capital and the life cycle of earnings. J. Political Econ. 75:4352–65
    [Google Scholar]
  18. Bennetts SK, Mensah FK, Westrupp EM, Hackworth NJ, Reilly S 2016. The agreement between parent-reported and directly measured child language and parenting behaviors. Front. Psychol. 7:1710
    [Google Scholar]
  19. Blanton H, Jaccard J. 2006. Arbitrary metrics in psychology. Am. Psychol. 62:27–41
    [Google Scholar]
  20. Bond TN, Lang K. 2013. The evolution of the black-white test score gap in grades K-3: the fragility of results. Rev. Econ. Stat. 95:1468–79
    [Google Scholar]
  21. Bond TN, Lang K. 2018. The black-white education scaled test-score gap in grades K-7. J. Hum. Resourc. 53:4891–917
    [Google Scholar]
  22. Bond TN, Lang K. 2019. The sad truth about happiness scales. J. Political Econ. 127:41629–40
    [Google Scholar]
  23. Boneva T, Rauh C. 2018. Parental beliefs about returns to educational investments—the later the better?. J. Eur. Econ. Assoc. 16:61669–711
    [Google Scholar]
  24. Bonhomme S, Robin JM. 2009. Consistent noisy independent component analysis. J. Econom. 149:112–25
    [Google Scholar]
  25. Brocas I, Carrilo J. 2018. The determinants of strategic thinking in preschool children. PLOS ONE 13:5 https://doi.org/10.1371/journal.pone.0195456
    [Crossref] [Google Scholar]
  26. Brocas I, Carrilo J. 2020. The development of social strategic ignorance and other regarding behavior from childhood to adulthood. J. Behav. Exp. Econ. 85:101524
    [Google Scholar]
  27. Carpenter M, Nagell K, Tomasello M. 1998. Social cognition, joint attention, and communicative competence from 9 to 15 months of age. Monogr. Soc. Res. Child Dev. 63:41–143
    [Google Scholar]
  28. Cattell RB. 1963. Theory of fluid and crystallized intelligence: a critical experiment. J. Educ. Psychol. 54:11–22
    [Google Scholar]
  29. Caucutt EM, Lochner L. 2020. Early and late human capital investments, borrowing constraints, and the family. J. Political Econ. 128:31065–147
    [Google Scholar]
  30. Cawley J, Heckman J, Vytlacil E. 1999. On policies to reward the value added by educators. Rev. Econ. Stat. 81:4720–27
    [Google Scholar]
  31. Charness G, List JA, Rustichini A, Samek A, Van De Ven J. 2019. Theory of mind among disadvantaged children: evidence from a field experiment. J. Econ. Behav. Organ. 166:174–94
    [Google Scholar]
  32. Chen X, Hong H, Nekipelov D. 2011. Nonlinear models of measurement errors. J. Econ. Lit. 49:4901–37
    [Google Scholar]
  33. Chetty R, Friedman JN, Rockoff JE. 2014. Measuring the impacts of teachers II: teacher value-added and student outcomes in adulthood. Am. Econ. Rev. 104:92633–79
    [Google Scholar]
  34. Chorniy A, Currie J, Sonchak L. 2020. Does prenatal WIC participation improve child outcomes?. Am. J. Health Econ. 6:2169–98
    [Google Scholar]
  35. Chrisman NR. 1998. Rethinking levels of measurement for cartography. Cartogr. Geogr. Inform. Syst. 25:4231–42
    [Google Scholar]
  36. Croon M. 2002. Using predicted latent scores in general latent structure models. Latent Variables and Latent Structure Models GA Marcoulides, I Moustaki 195–224 Mahwah, NJ: Lawrence Erlbaum
    [Google Scholar]
  37. Cunha F, Elo I, Culhane J. 2013. Eliciting maternal beliefs about the technology of skill formation NBER Work. Pap. 19144
    [Google Scholar]
  38. Cunha F, Gerdes M, Nihtianova S. 2020. Language environment and maternal expectations: an evaluation of the Lena Start program Work. Pap., Rice Univ. Houston, TX:
    [Google Scholar]
  39. Cunha F, Heckman JJ. 2007. The technology of skill formation. Am. Econ. Rev. 97:231–47
    [Google Scholar]
  40. Cunha F, Heckman JJ. 2008. Formulating, identifying and estimating the technology of cognitive and noncognitive skill formation. J. Hum. Resourc. 43:4738–82
    [Google Scholar]
  41. Cunha F, Heckman JJ, Schennach S. 2010. Estimating the technology of cognitive and noncognitive skill formation. Econometrica 78:883–931
    [Google Scholar]
  42. Cunha F, Nihtianova S. 2020. Measuring early investments in language development Work. Pap., Rice Univ. Houston, TX:
    [Google Scholar]
  43. Cunha F, Wolpin KI. 2020. An evaluation of the Alief Independent School District JumpStart program: using a model to recover mechanisms from an RCT Work. Pap., Tex. Policy Lab, Rice Univ. Houston:
    [Google Scholar]
  44. Currie J. 2013. Pollution and infant health. Child Dev. Perspect. 7:4237–42
    [Google Scholar]
  45. de Villiers JG, de Villiers PA. 2014. The role of language in theory of mind development. Top. Lang. Disord. 34:4313–28
    [Google Scholar]
  46. Del Boca D, Flinn C, Wiswall MJ 2014. Household choices and child development. Rev. Econ. Stud. 81:1137–85
    [Google Scholar]
  47. Eimas PD, Miller JL. 1992. Organization in the perception of speech by young infants. Psychol. Sci. Public Interest 3:6340–45
    [Google Scholar]
  48. Embrey I. 2019. Re-estimating the technology of cognitive and noncognitive skill formation Work. Pap., Lancaster Univ Lancaster, UK:
    [Google Scholar]
  49. Gertler P, Heckman J, Pinto R, Zanolini A, Vermeersch C et al. 2014. Labor market returns to an early childhood stimulation intervention in Jamaica. Science 344:6187998–1001
    [Google Scholar]
  50. Gilkerson J, Richards JA, Warren SF, Oller DK, Russo R, Vohr B. 2018. Language experience in the second year of life and language outcomes in late childhood. Pediatrics 142:4e20174276
    [Google Scholar]
  51. Hall RE, Jones CI. 1999. Why do some countries produce so much more output per worker than others?. Q. J. Econ. 114:183–116
    [Google Scholar]
  52. Hansen KT, Heckman JJ, Mullen KJ. 2004. The effect of schooling and ability on achievement test scores. J. Econom. 121:1–239–98
    [Google Scholar]
  53. Hart B, Risley T. 1995. Meaningful Differences in the Everyday Experience of Young American Children Baltimore, MD: Paul H. Brookes
    [Google Scholar]
  54. Heckman JJ, Karapacula G. 2019a. Intergenerational and intragenerational externalities of the Perry Preschool Project NBER Work. Pap. 25889
    [Google Scholar]
  55. Heckman JJ, Karapacula G. 2019b. The Perry preschoolers at late midlife: a study in design-specific inference HCEO Work. Pap. 2019-034 Univ. Chicago Chicago:
    [Google Scholar]
  56. Heckman JJ, Lochner L, Taber C. 1998. Explaining rising wage inequality: explorations with a dynamic general equilibrium model of labor earnings with heterogeneous agents. Rev. Econ. Dyn. 1:11–58
    [Google Scholar]
  57. Heckman JJ, Mosso S. 2014. The economics of human development and social mobility. Annu. Rev. Econ. 6:689–733
    [Google Scholar]
  58. Heckman JJ, Pinto R, Savelyev P. 2013. Understanding the mechanisms through which an influential early childhood program boosted adult outcomes. Am. Econ. Rev. 103:62052–86
    [Google Scholar]
  59. Heckman JJ, Schennach MS, Williams B 2010. Matching with error-laden covariates Unpublished manuscript Univ. Chicago Chicago:
    [Google Scholar]
  60. Heckman JJ, Stixrud J, Urzua S. 2006. The effects of cognitive and noncognitive abilities on labor market outcomes and social behavior. J. Lab. Econ. 24:3411–82
    [Google Scholar]
  61. Ho A. 2009. A nonparametric framework for comparing trends and gaps across tests. J. Educ. Behav. Stat. 34:201–28
    [Google Scholar]
  62. Ho A, Quinn D. 2020. Ordinal approaches to decomposing between-group test score disparities Work. Pap. 20-257 Annenberg Inst., Brown Univ. Providence, RI:
    [Google Scholar]
  63. Ho A, Reardon S. 2012. Estimating achievement gaps from test scores reported in ordinal “proficiency” categories. J. Educ. Behav. Stat. 37:4489–517
    [Google Scholar]
  64. Hoderlein S, Winter J. 2010. Structural measurement errors in nonseparable models. J. Econom. 157:432–40
    [Google Scholar]
  65. Hu Y, Schennach SM. 2008. Instrumental variable treatment of nonclassical measurement error models. Econometrica 76:2195–216
    [Google Scholar]
  66. Jacob B, Rothstein J. 2016. The measurement of student ability in modern assessment systems. J. Econ. Perspect. 30:85–108
    [Google Scholar]
  67. Joreskog KG, Goldberger AS. 1975. Estimation of a model with multiple indicators and multiple causes of a single latent variable. J. Am. Stat. Assoc. 70:631–39
    [Google Scholar]
  68. Junker B, Schofield LS, Taylor LJ. 2012. The use of cognitive ability measures as explanatory variables in regression analysis. IZA J. Lab. Econ. 1:14
    [Google Scholar]
  69. Kalil A 2014. Inequality begins at home: the role of parenting in the diverging destinies of rich and poor children. Families in an Era of Increasing Inequality: Diverging Destinies PR Amato, A Booth, SM McHale, J Van Hook 63–82 New York: Springer
    [Google Scholar]
  70. Kuhl PK. 2004. Early language acquisition: cracking the speech code. Nat. Rev. Neurosci. 5:831–43
    [Google Scholar]
  71. Kuhl PK, Tsao FM, Liu HM 2003. Foreign-language experience in infancy: effects of short-term exposure and social interaction on phonetic learning. PNAS 100:159096–101
    [Google Scholar]
  72. Kuhl PK, Williams KA, Lacerda F, Stevens KN, Lindblom B. 1992. Linguistic experience alters phonetic perception in infants by 6 months of age. Science 255:5044606
    [Google Scholar]
  73. La Porta R, Lopez-de Silanes F, Shleifer A, Vishny R 1999. The quality of government. J. Law Econ. Organ. 15:1222–79
    [Google Scholar]
  74. Lang K. 2010. Measurement matters: perspectives on education policy from an economist and school board member. J. Econ. Perspect. 24:167–81
    [Google Scholar]
  75. Lockwood JR, McCaffrey D. 2014. Correcting for test score measurement error in ANCOVA models for estimating treatment effects. J. Educ. Behav. Stat. 39:122–52
    [Google Scholar]
  76. Lord F. 1975. The “ability” scale in item characteristics curve theory. Psychometrika 40:205–17
    [Google Scholar]
  77. Lucas RE. 1988. On the mechanics of economic development. J. Monet. Econ. 22:13–42
    [Google Scholar]
  78. Mauro P. 1995. Corruption and growth. Q. J. Econ. 110:3681–712
    [Google Scholar]
  79. McCoy DC, Waldman M, Altafim E, Brentani A, Castellanos A et al. 2018. Measuring early childhood development at a global scale: evidence from the caregiver-reported early development instruments. Early Childh. Res. Q. 45:58–68
    [Google Scholar]
  80. Moens MA, Weeland J, Giessen DVd, Chhangur RR, Overbeek G. 2018. In the eye of the beholder? Parent-observer discrepancies in parenting and child disruptive behavior assessments. J. Abnorm. Child Psychol. 46:1147–59
    [Google Scholar]
  81. Mosteller F, Turkey JW. 1977. Data Analysis and Regression: A Second Course in Statistics Reading, MA: Addison-Wesley
    [Google Scholar]
  82. Nielsen E. 2015a. Achievement gap estimates and deviations from cardinal comparability Finance Econ. Discuss. Ser. 2015-040 Fed. Reserve Board Washington, DC:
    [Google Scholar]
  83. Nielsen E. 2015b. The income-achievement gap and adult outcome inequality Finance Econ. Discuss. Ser. 2015-041 Fed. Reserve Board Washington, DC:
    [Google Scholar]
  84. Nielsen E. 2019. Test questions, economic outcomes, and inequality Finance Econ. Discuss. Ser. 2019-013 Fed. Reserve Board Washington, DC:
    [Google Scholar]
  85. Olds D. 2002. Prenatal and infancy home visiting by nurses: from randomized trials to community replication. Prev. Sci. 3:3153–72
    [Google Scholar]
  86. Olley S, Pakes A. 1996. The dynamics of productivity in the telecommunications equipment industry. Econometrica 64:61263–97
    [Google Scholar]
  87. Polachek SW, Das T, Thamma-Apiroam R. 2016. Micro- and macroeconomic implications of heterogeneity in the production of human capital. J. Political Econ. 123:61410–55
    [Google Scholar]
  88. Reiersol O. 1950. On the identifiability of parameters in Thurstone's multiple factor analysis. Psychometrika 15:2121–49
    [Google Scholar]
  89. Roggman LA, Cook GA, Innocenti MS, Norman VJ, Christiansen K. 2013. Parenting interactions with children: checklist of observations linked to outcomes (PICCOLO) in diverse ethnic groups. Infant Mental Health J. 34:4290–306
    [Google Scholar]
  90. Rothstein J. 2010. Teacher quality in educational production: tracking, decay, and student achievement. Q. J. Econ. 125:1175–214
    [Google Scholar]
  91. Schennach SM. 2016. Recent advances in the measurement error literature. Annu. Rev. Econ. 8:341–77
    [Google Scholar]
  92. Schofield L. 2014. Measurement error in the AFQT in the NLSY79. Econ. Lett. 123:3262–65
    [Google Scholar]
  93. Schröder C, Yitzhaki S. 2017. Revisiting the evidence for cardinal treatment of ordinal variables. Eur. Econ. Rev. 92:337–58
    [Google Scholar]
  94. Segal C. 2012. Working when no one is watching: motivation, test scores, and economic success. Manag. Sci. 58:1438–57
    [Google Scholar]
  95. Sijtsma K, Junker BW. 2006. Item response theory: past performance, present developments, and future expectations. Behaviormetrika 33:175–102
    [Google Scholar]
  96. Stevens S. 1946. On the theory of scales of measurement. Science 103:677–80
    [Google Scholar]
  97. Suskind DL, Leffel KR, Graf E, Hernandez MW, Gunderson EA et al. 2015. A parent-directed language intervention for children of low socioeconomic status: a randomized controlled pilot study. J. Child Lang. 43:2366–406
    [Google Scholar]
  98. Thorndike RL 1951. Reliability. Educational Measurement EF Lindquist, RL Thorndike 560–620 Washington, DC: Am. Counc. Educ.
    [Google Scholar]
  99. Todd PE, Wolpin KI. 2003. On the specification and estimation of the production function for cognitive achievement. Econ. J. 113:485F3–33
    [Google Scholar]
  100. Todd PE, Wolpin KI. 2007. Production of cognitive achievement in children: home, school, and racial test score gaps. J. Hum. Capital 1:191–113
    [Google Scholar]
  101. Tomasello M 1995. Joint attention as social cognition. Joint Attention: Its Origins and Role in Development C Moore, PJ Dunham 103–30 Mahwah, NJ: Lawrence Erlbaum
    [Google Scholar]
  102. Tomasello M, Carpenter M, Call J, Behne T, Moll H. 2005. Understanding and sharing intentions: the origins of cultural cognition. Behav. Brain Sci. 28:5675–91
    [Google Scholar]
  103. van der Linden WJ, Hambleton RK. 2013. Handbook of Modern Item Response Theory New York: Springer
    [Google Scholar]
  104. Wansbeek T, Meijer E. 2001. Measurement Error and Latent Variables Amsterdam: North Holland
    [Google Scholar]
  105. Werker JF, Gilbert JHV, Humphrey K, Tees RC. 1981. Developmental aspects of cross-language speech perception. Child Dev. Perspect. 52:1349–55
    [Google Scholar]
  106. Werker JF, Tees RC. 2005. Speech perception as a window for understanding plasticity and commitment in language systems of the brain. Dev. Psychobiol. 46:233–51
    [Google Scholar]
  107. Williams B. 2019. Controlling for ability using test scores. J. Appl. Econom. 34:4547–65
    [Google Scholar]
  108. Williams B. 2020. Identification of the linear factor model. Econom. Rev. 39:192–109
    [Google Scholar]
/content/journals/10.1146/annurev-economics-080217-053409
Loading
/content/journals/10.1146/annurev-economics-080217-053409
Loading

Data & Media loading...

  • Article Type: Review Article
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error