Learning about heterogeneity in returns to schooling

Gary Koop, Justin L. Tobias

Research output: Contribution to journalArticle

22 Citations (Scopus)

Abstract

Using data from the National Longitudinal Survey of Youth (NLSY) we introduce and estimate various Bayesian hierarchical models that investigate the nature of unobserved heterogeneity in returns to schooling. We consider a variety of possible forms for the heterogeneity, some motivated by previous theoretical and empirical work and some new ones, and let the data decide among the competing specifications. Empirical results indicate that heterogeneity is present in returns to education. Furthermore, we find strong evidence that the heterogeneity follows a continuous rather than a discrete distribution, and that bivariate normality provides a very reasonable description of individual-level heterogeneity in intercepts and returns to schooling.
LanguageEnglish
Pages827-849
Number of pages23
JournalJournal of Applied Econometrics
Volume19
Issue number7
DOIs
Publication statusPublished - 2004

Fingerprint

learning
normality
Returns to schooling
evidence
education
Bayesian hierarchical model
Normality
Returns to education
Unobserved heterogeneity
Empirical results
Discrete distributions

Keywords

  • economics
  • econometrics
  • statistics
  • finance
  • schoolong
  • bayesian analysis

Cite this

Koop, Gary ; Tobias, Justin L. / Learning about heterogeneity in returns to schooling. In: Journal of Applied Econometrics. 2004 ; Vol. 19, No. 7. pp. 827-849.
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Learning about heterogeneity in returns to schooling. / Koop, Gary; Tobias, Justin L.

In: Journal of Applied Econometrics, Vol. 19, No. 7, 2004, p. 827-849.

Research output: Contribution to journalArticle

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AU - Tobias, Justin L.

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