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Pregnancy Medicaid Expansions and Fertility: Differentiating Between the Intensive and Extensive Margins

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Abstract

The theoretical and empirical links between public health insurance access and fertility in the United States remain unclear. Utilizing a demographic cell-based estimation approach with panel data (1987–1997), we revisit the large-scale Medicaid expansions to pregnant women during the 1980s to estimate the heterogeneous impacts of public health insurance access on childbirth. While the decision to become a parent (i.e., the extensive margin) appears to be unaffected by increased access to Medicaid, we find that increased access to public health insurance positively influenced the number of high parity births (i.e., the intensive margin) for select groups of women. In particular, we find a robust, positive birth effect for unmarried women with a high school education, a result which is consistent across the two racial groups examined in our analysis: African American and white women. This result suggests that investigating effects along both the intensive and extensive margin is important for scholars who study the natalist effects of social welfare policies, and our evidence provides a more nuanced understanding of the influence of public health insurance on fertility.

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Notes

  1. DeLeire et al. (2011) provide one online table that investigates first births along as a robustness check. They do not, however, run models with higher-parity births separately.

  2. The RAND HIE had three different cost-sharing plans, but because the policies had a maximum out-of-pocket expenditure, most members of the control group paid approximately $1000 for their insurance coverage.

  3. Both outcome variables are estimated using the natural log of the birth measure.

  4. In the early period, education data were not collected in California, New York, Texas, and Washington. Zavodny and Bitler (2010) exclude these observations when examining models by mother’s education; however, we recover these observations using the methodology outlined in the Appendix.

  5. While it is possible that some uninsured women would not have had to pay the full cost of birth in the absence of expanded Medicaid, it is still the case that discounted prices or limited charity care would likely be inferior to a fully covered Medicaid birth.

  6. As noted earlier, the Medicaid program in the United States dates back to 1965. It is designed as a state and federal partnership, whereby states receive significant federal funds to offset healthcare costs borne at the local level. In exchange for these federal funds, states were mandated to provide select services and cover select populations and, in the initial years, the administration of the state-level public health insurance program (Medicaid) was typically linked to the state-level cash assistance program (AFDC). Both the population and services have change greatly over time—the increase in generosity for the former is the natural experiment we examine in this analysis.

  7. The annual expansions are as follows: the Deficit Reduction Act of 1984, the Consolidated Omnibus Budget Reconciliation Act of 1985, the Omnibus Reconciliation Act of 1986, the Omnibus Reconciliation Act of 1987, the Medicare Catastrophic Act of 1988, and the Omnibus Reconciliation Act of 1989.

  8. In the earlier years, these thresholds were often set in dollars rather than percent of FPL. We use Hill (1992) as the primary source for thresholds in the early period, and follow him in taking the maximum of the AFDC Payment Standard and the Medically Needy Income threshold and then dividing by the annual FPL to generate the numbers reported in the table.

  9. Annual thresholds are provided by state-year in Table 1 of the Appendix ESM.

  10. We aggregate data to the quarterly level to allow for threshold changes occurring throughout the course of a given year. Additionally, note that married women became categorically eligible on July 1, 1986 (though still subject to the income test). Allowing 9 months for gestation, this means that the first observation in estimation will be in 1987.

  11. As a specification check, we also estimated models breaking age up into three groups: 20–27, 28–34, and 35 and older. Results were nearly identical.

  12. Initially, we do not separate cells by marital status since it is endogenous with the fertility choice. Because unmarried women have lower incomes than married women, all else equal, we provide results separating married and unmarried women as a robustness check. As we show below, this distinction is important so all sample size counts reported include a distinction between married and unmarried women.

  13. In the Vital Statistics data, reporting of mother’s educational attainment was not mandated until 1992. Thus, for some large states—namely California, New York, Texas, and Washington—data are missing in this early period. To recover these observations, we use an allocation algorithm as outlined in the Appendix ESM.

  14. Similar to DeLeire et al. (2011), we estimate the models through 1997 to allow a sufficient period for estimation. Given the demographic cells outlined in Table 1, this implies a maximum number of 43 * (51 * 2 * 2 * 3 * 3 * 2) = 43 * 3672 = 157,896 aggregated observations for analysis. However, we were concerned about including time series for cells with zero counts in some years. Small change for these cells over time could produce very large proportionate changes. As a result, we fix the panel at the most disaggregated level to only those cells which have sample weights over the entire duration of our analysis. With this restriction, the number of demographic cells declines from 3672 to 3435, yielding a maximum of 147,705 observations. Additionally, this choice excludes just 3357 of the underlying 35,253,495 births used to create the demographic cells.

  15. The source of this data is IPUMS USA (Ruggles et al. 2015).

  16. See DeLeire et al. (2011) for details.

  17. We also ran a set of models that exclude these policy measures, and the results were substantively identical.

  18. For example, Cutler and Gruber (1996) report that 25 percent of child Medicaid participants in their sample were imputed to be ineligible.

  19. Table 4 should be compared to Tables A3 and A4 in the Appendix.

  20. Data come from CDC Public Use Data Tape Documentation—available online @ ftp://ftp.cdc.gov/pub/Health_Statistics/NCHS/Dataset_Documentation/DVS/natality/Nat1990doc.pdf.

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Authors and Affiliations

  1. Institute for Research on Poverty, University of Wisconsin-Madison, Madison, WI, USA

    Lincoln H. Groves

  2. Public Administration and International Affairs, Center for Policy Research, Syracuse University, Syracuse, NY, USA

    Sarah Hamersma

  3. Public Administration and International Affairs, Maxwell X Lab, Center for Policy Research, Syracuse University, Syracuse, NY, USA

    Leonard M. Lopoo

Authors
  1. Lincoln H. Groves
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  2. Sarah Hamersma
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  3. Leonard M. Lopoo
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Correspondence to Leonard M. Lopoo.

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Groves, L.H., Hamersma, S. & Lopoo, L.M. Pregnancy Medicaid Expansions and Fertility: Differentiating Between the Intensive and Extensive Margins. Popul Res Policy Rev 37, 461–484 (2018). https://doi.org/10.1007/s11113-018-9465-5

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