Selection and the Marriage Premium for Infant Health


Previous research has found a positive relationship between marriage and infant health, but it is unclear whether this relationship is causal or a reflection of positive selection into marriage. We use multiple empirical approaches to address this issue. First, using a technique developed by Gelbach (2009) to determine the relative importance of observable characteristics, we show how selection into marriage has changed over time. Second, we construct a matched sample of children born to the same mother and apply panel data techniques to account for time-invariant unobserved characteristics. We find evidence of a sizable marriage premium. However, this premium fell by more than 40 % between 1989 and 2004, largely as a result of declining selection into marriage by race. Accounting for selection reduces ordinary least squares estimates of the marriage premiums for birth weight, prematurity, and infant mortality by at least one-half.

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  1. 1.

    Throughout the article, we use the term “selection” to refer to the marriage decision. There may also be selection into the sample if the likelihood of having a live birth conditional on a pregnancy is correlated with the mother’s characteristics. Women may select out of the sample through abortion; rates of abortion fell for both single and married women between 1980 and 2004 (Jones et al. 2009); and between 1994 and 2008, the fraction of women receiving abortions who were married declined from 18.4 to 14.8 (Jones et al. 2002, 2010). It is unclear, however, how selection into abortion varies by marital status, and we are therefore unable to determine how this type of selection would affect our results.

  2. 2.

    For example, the Administration for Children and Family’s Healthy Marriage Initiative is motivated by the 1996 Congressional finding that “marriage is an essential institution of a successful society which promotes the interests of children.”

  3. 3.

    Although not the focus of their studies, Royer (2004) and Abrevaya and Dahl (2008) provided fixed-effects estimates of the effect of marriage on infant health using state-level data linking birth certificates.

  4. 4.

    Two notable papers that have used an instrumental variables specification for marriage are Finlay and Neumark (2010) and Dahl (2010). Finlay and Neumark used incarceration rates as an instrument for marriage, and Dahl used state variation in minimum age requirements for marriage. Interestingly, both studies found that for women whose decision to marry is affected by these instruments (and who are generally low socioeconomic status), marriage has negative effects on outcomes.

  5. 5.

    Prior to 1985, a few states reported only 50 % of the birth certificate data.

  6. 6.

    A “shotgun” wedding occurs when a couple is forced to marry to avoid the embarrassment from a nonmarital pregnancy.

  7. 7.

    We have also produced results that stratify the sample by education and maternal age. Because the results are qualitatively similar to those for the full sample, we omit them here for brevity.

  8. 8.

    We use the five-minute Apgar score, which is an assessment of the infant’s overall health 5 minutes after birth, using a 10-point scale. All data are from the 1989–2004 Natality Detail Files, with the exception of infant mortality, for which we use the Vital Statistics linked infant death/birth certificate data from 1989–1991 and 1995–2002. The NCHS did not produce these data for 1992–1994.

  9. 9.

    Cells are defined by single year of age, single year of education, birth order, race, state, birth year, and marital status.

  10. 10.

    See Buckles and Hungerman (forthcoming) for a more detailed explanation.

  11. 11.

    Two previous studies have used similar approaches to create longitudinal data set using the Natality Detail Files. Currie and Moretti (2002) used first and second births from the 1970–1999 files to estimate the effect of education on infant health. Abrevaya (2006) matched mothers for a restricted subset of state pairs (using smaller states) for 1990–1998 to estimate the effects of maternal smoking.

  12. 12.

    Matched infants are more likely to be black, which is associated with worse infant health, but their mothers are more likely to be in their 20s and 30s, which is associated with better infant health. We have no reason to think that being from a smaller state would be systematically related to infant health.

  13. 13.

    We use birth weight as our measure of infant health in all figures because it is a widely used measure that captures trends in the entire distribution of infant health. Results are similar using the alternative measures.

  14. 14.

    The relationship between mother’s age and birth weights is actually quadratic, with a peak occurring at around age 32. The average age for married mothers increased from 27.7 in 1989 to 29.4 in 2004, which is still in the range where increasing maternal age is associated with higher birth weights.

  15. 15.

    We omit the fixed effects because the Altonji et al. method requires that the observables are drawn randomly from the full set of characteristics that determine the outcome. Conceptually, we think that state and year fixed effects might violate this assumption; practically, it makes almost no difference because these covariates explain very little of the variation in infant health.

  16. 16.

    In the earlier analysis, we treat mother’s health as exogenous because many of the health conditions identified are chronic (such as chronic hypertension, renal and cardiac disease, and some diabetes). However, the mother’s health is also a mechanism through which marriage could affect infant health. Because the aforementioned results consider mother’s health separately, one could easily approximate the effect of treating health as a mechanism rather than as a channel for selection.

  17. 17.

    To increase the number of cells in the natality data with a match in the CPS data, we use five-year of age cells and education cells defined by degree status.

  18. 18.

    Wu and Hart (2002) found that transitions out of marriage are associated with decreases in physical and mental health.

  19. 19.

    The coefficient on the dummy variable indicating that the woman was unmarried for both births is small in magnitude and statistically insignificant for whites but is statistically significant for blacks. Black women who were unmarried for both births saw a greater decrease in infant health than those who were married for both, which may indicate that time-varying factors that affect infant health worsen over time for single black women.

  20. 20.

    For another comparison, nonmarital childbearing is associated with a 67 % increase in the rate of low birth weight, and interpregnancy intervals of 3 rather than 18 months are associated with a 49 % increase (Conde-Agudelo et al. 2006).

  21. 21.

    Demographers should find the Gelbach approach useful for accounting for selection bias in a variety of other settings as well.


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This article has benefitted from the research assistance of Alan Gelder, Phillip Manwaring, Angie Otteson, Craig Palsson, and Kristy Parkinson. We are thankful for comments from Bill Evans, Dan Hungerman, Lucie Schmidt, and participants in seminars at the University of Washington, University of Notre Dame, Brigham Young University, University of Miami, Baylor University, and the 2011 Southern Economics Association Meetings.

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Correspondence to Kasey S. Buckles.

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Buckles, K.S., Price, J. Selection and the Marriage Premium for Infant Health. Demography 50, 1315–1339 (2013).

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  • Marriage
  • Marriage premium
  • Infant health
  • Birth weight
  • Prematurity