|Title||The Effects of DACA on Pregnancy Outcomes in California|
|C1 Background and Explanation of Rationale||
The DACA program was passed by Executive Order on June 15, 2012. DACA provided temporary protection against deportation and work permits for individuals who were undocumented, had arrived in the US at < 16 years of age, and were younger than 31 years of age on June 15, 2012. To be DACA-eligible, individuals additionally had to have resided in the US since 2007, be enrolled in school or hold a GED, and have never been convicted of a felony or > 3 misdemeanors. The fate of the DACA program is currently under discussion, making this research very pertinent to ongoing policymaking.
Quasi-experimental and other observational research has uncovered evidence of positive effects of DACA on the psychological wellbeing of recipients.1,2 Quasi-experimental research has also demonstrated causal effects of DACA on better mental health for the children of recipients.3 Potential pathways linking DACA to improved health include its positive effects on employment outcomes,4 as well as reductions in worry about deportation. Worry about deportation, as with other chronic stressors, may have negative consequences on multiple body systems,5 and may result in foregoing necessary medical care.
No research, to our knowledge, has examined the relationship between DACA and birth outcomes, including preterm birth. Scholars have linked immigration-related stressors (e.g. prenatal exposure to immigration raids, the passage of restrictive immigration policies) to birth outcomes.6,7 In addition, researchers have uncovered improvements in prenatal care and birth outcomes as the result of an inclusive policy that expanded healthcare access for pregnant undocumented women.8
|C2 What are the hypotheses to be tested?||We will quantify the effect of the Deferred Action for Childhood Arrivals (DACA) immigration policy on the composition of births and birth outcomes among infants born to likely eligible mothers as compared to infants born to demographically similar mothers who would have been ineligible based on date of birth.|
|C3 How will these hypotheses be tested? *||
We propose to estimate the effects of DACA on pregnancy outcomes for likely DACA-eligible women and their infants in California, using California birth records data. We propose to use a quasi-experimental strategy that will allow us to evaluate the effects of DACA. We note, however, that power calculations using simulated data suggests that we will not be sufficiently powered to detect small effects of DACA using California birth records alone – and may need to expand to a national analysis.
The ideal design for this study would follow the regression discontinuity approach employed by Hainmueller et al3 and compare differences in birth outcomes after DACA passage for foreign-born women just above/below the birthdate cutoff (June 19, 1981). Nevertheless, power calculations using simulated data indicate that we would be only powered to detect unrealistically large (e.g. 1 standard deviation) with this strategy, in part because of the relatively low uptake of DACA among women who would be classified as DACA recipients.
We therefore propose to use a difference-in-differences (DID) design, a quasi-experimental technique well suited to examining the effects of policies among population subgroups while adjusting for secular trends in a “control” group of similar individuals. In particular, we will compare overall birth outcomes both before and after the passage of DACA among likely DACA-eligible women, “differencing out” secular trends among women who are otherwise demographically similar (e.g. non-US born) but are ineligible because they missed the birthdate cut-off. In this approach, women will be identified as likely eligible or ineligible based on demographic characteristics (e.g. foreign-born, maternal ethnicity, educational characteristics, area of residence), age (i.e. < 31 years of age versus > 31 before June 15, 2012), and payment source listed in the birth record (if available).
While the DID design is better powered, it comes with assumptions that trends in outcomes for treatment and control groups would otherwise be similar if it were not for DACA passage/implementation and that DACA implementation would not contribute to changes in the composition of births (e.g. by maternal characteristics) for treatment or control groups. These assumptions may be unrealistic, particularly given that DACA was linked to improved labor market and economic outcomes – both of which may have influenced fertility.9 To our knowledge, one study has demonstrated reduced fertility among adolescent girls/young women after DACA implementation.9
While the parallel trends assumption cannot be directly tested, we will evaluate whether trends in each of the birth outcomes (listed below) looked similar at 1 and 2 years pre-DACA passage for treatment and control groups using California birth records. We will additionally evaluate the effect of DACA on the composition of births (e.g. by maternal age, educational attainment, marital status, male-to-female infant sex ratio). Finally, we will evaluate effects of DACA on fertility using appropriate denominators from the American Community Survey.
If assumptions appear to be met, we will move forward with evaluating the effects of DACA on the birth outcomes listed below. In either case, we will report on any effects of DACA on the composition of births.
|C4 Country||United States|
|C5 Scale (# of Units)||Sample size is determined by the number of births in California birth certificate data that meet eligibility criteria|
|C6 Was a power analysis conducted prior to data collection?||Yes|
|C7 Has this research received Insitutional Review Board (IRB) or ethics committee approval?||Use of California birth certificate data by CSU Fresno/Central Valley Health Policy Institute colleagues has been approved by the CSU Fresno IRB.|
|C8 IRB Number||not provided by authors|
|C9 Date of IRB Approval||not provided by authors|
|C10 Will the intervention be implemented by the researcher or a third party?||Researchers|
|C11 Did any of the research team receive remuneration from the implementing agency for taking part in this research?||not provided by authors|
|C12 If relevant, is there an advance agreement with the implementation group that all results can be published?||not provided by authors|
|C13 JEL Classification(s)||not provided by authors|