Selection works both ways: BMI and marital formation among young women

Abstract

The literature on entry into marriages has almost universally regarded a high body mass index (BMI) to be a disadvantage for women in the marriage market. But the theoretical effect of BMI on marital entry is actually uncertain because women who anticipate poor outcomes in the marriage market are more likely to accept early offers, while women with more desirable characteristics can afford to wait for a better match. Using data from the 1997 National Longitudinal Survey of Youth, we show that female entry into marriage does decline as BMI rises, but that early marriage is nonlinear in BMI. Women with an extremely high BMI or with a BMI in the most attractive range are less likely to marry early.

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Notes

  1. 1.

    All aggregate statistics are from the National Center of Health Statistics.

  2. 2.

    For men, income appears to matter more than physical characteristics.

  3. 3.

    There are improvements in some health outcomes, including mental health and alcohol abuse.

  4. 4.

    There are also negative consequences in the employment market. Hammermesh and Biddle (1994) is the seminal paper. This effect, of course, can spill over into the marriage market because it affects potential gains from marriage.

  5. 5.

    The authors do point out that this effect is theoretically ambiguous. It is also plausible that black women in these conditions might increase their investment in marriageability because men are on the short side of the market.

  6. 6.

    We here index female desirability with variations in arrival probability p and assume that all women have access to the same match distribution f(x). We could alternatively index desirability by variations in the quality of matches that women receive. The qualitative nature of the results is similar.

  7. 7.

    There is some attrition in the NLSY97 sample. The NLSY retention rate for women exceeds 85 % for all years of our sample. The NLSY website contains an extensive discussion of attrition in the NLSY sample.

  8. 8.

    In various years, between 6 and 118 observations were dropped for a BMI out of range: less than 3 % of the sample in any given year.

  9. 9.

    The full results are available upon request from the author.

  10. 10.

    Average Engagement Length, and Other Wedding Planning Statistics (2013).

  11. 11.

    Fewer than 5 % of females from our sample, in any year, were unmarried and pregnant. We do not drop women who were pregnant at age X + 2, since the analysis focuses on the effect of BMI at age X on entry into marriages in succeeding periods.

  12. 12.

    All density estimations use a Gaussian kernel, with bandwidth calculated to minimize mean integrated square error.

  13. 13.

    The literature on the correlation between BMI and socioeconomic status is extensive. Baum and Ruhm (2009) investigate important intermediating factors.

  14. 14.

    We tried dropping approximately 5 % of the observations that were married at age 18 and 19, to detect potential reverse causation problems, but the results were almost the same.

  15. 15.

    Robinson (1988) first proposed this estimator and outlined its properties. We again use a Gaussian kernel for the nonparametric component, with bandwidth chosen to minimize mean square error.

  16. 16.

    There are too few marriages in each single year to fit a parametric model for marriages at each age, or even for two-year age intervals.

  17. 17.

    We again select two years because this is a typical engagement period.

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Correspondence to Michael Malcolm.

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Malcolm, M., Kaya, I. Selection works both ways: BMI and marital formation among young women. Rev Econ Household 14, 293–311 (2016). https://doi.org/10.1007/s11150-014-9247-8

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Keywords

  • BMI
  • Obesity
  • Marital formation

JEL Classification

  • I10
  • J12