Room: Phillips 203
Time: Mon 08:30 AM-10:00 AM

Birth and Fertility Models

Chair: Lan Liang (AHRQ)

Session Description

Understanding the determinants of fertility is of interest not only to health economics, but also to many other areas of economics and public policy. It is critical in understanding and predicting economic growth, labor supply, and even the gender wage gap. This session contains three contributions that analyze the role of technology in fertility decisions and infant health.

Burlando begins the session by presenting a natural experiment from Tanzania, where a month-long blackout led to a temporary reduction in refrigeration and maternal nutrition. The author shows that mothers who were pregnant during the blackout had babies who weighed 50 to 100 grams less at birth. This result is especially concerning since blackouts and similar risks are common in developing countries. In particular, this highlights scope for improving birth outcomes through better infrastructure and insurance against this type of risk.

The next two papers analyze infertility treatments, which is a problem more common in developed countries. A classic problem in the literature on infertility treatment is that women who decide to undergo infertility treatment may be unobservably different from women who do not undergo these treatments. Therefore, it is difficult to separate a causal effect of fertility on outcomes from a selection effect. Both papers in this session propose using state mandates to cover infertility treatment as an instrument to find a causal effect of infertility treatment.

Machado et al use this instrument to investigate the issue of women delaying child-bearing. They hypothesize that mandated infertility treatments may cause women to delay having children, knowing that they will not face the infertility risks that previous generations have faced. Hence, the number of children had by a family does not always increase after mandating infertility treatment.

Mookim et al use state mandates to better understand the risks a mother faces by undergoing infertility treatment. The existing literature has shown that that mothers who undergo these treatments face higher health risks. Using this instrument, Mookim et al find that there is no effect of treatment on health outcome, showing that the entire risk differential is driven by selection.

This session provides new insights into the role of risk and technology in fertility decisions, suggesting ways to improve childbirth outcomes as well as showing that infertility treatments are not as risky as once thought.

Key Terms None

Session Organizer: Randy Ellis (Boston University)

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Presentations

1. When the Lights Go Out: Permanent Health Effects of Transitory Shocks

   Presenter: Alfredo Burlando (Boston University)

   Discussant: Kosali Simon (Cornell University)

2. Coverage of Infertility Treatment and Fertility Outcomes: Do Women Catch Up?

   Presenter: Matilde Machado (Universidad Carlos III de Madrid)

   Discussant: Monica Galizzi (University of Massachusetts)

3. Infertility Treatment, ART and IUI Procedures and Delivery Outcomes: How Important is Selection?

   Presenter: Pooja Mookim (Boston University)

   Discussant: Marianne Bitler (University of California, Irvine)