Returns to women’s education using optimal IV selection

Jun Sung Kim, Bin Jiang, Chuhui Li, Hee Seung Yang

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3 Citations (Scopus)

Abstract

This paper investigates returns to women’s education by applying an optimal IV selection approach, post-Lasso IV estimation, which improves the first-stage predictive relationship between an endogenous regressor and instruments. Using the 2010 American Community Survey, we find that an extra year of education increases married women’s own income by $4,480 and spouse income by $8,822. Our findings indicate that 53% of the increase in women’s consumption by education is attributed to the marriage market, and thus, we conclude that the marriage market is the primary channel through which education improves women’s well-being. The results demonstrate the advantages of the post-Lasso approach: The resulting two-stage least squares estimator maintains efficiency without increasing finite sample bias and is less subject to the inconsistency problem when some instruments are invalid; This differs from the results using the instrument of birth quarters only, which is mostly applied in studies on returns to education.

Original languageEnglish
Pages (from-to)815-830
Number of pages16
JournalApplied Economics
Volume51
Issue number8
DOIs
Publication statusPublished - 2019

Keywords

  • Instrumental variables estimation
  • optimal instruments
  • post-Lasso
  • returns to women’s education
  • spouse income

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