This is the fourth presentation in a series of gallery talks that highlight a collage in its current exhibition, Artists in the Archives: Unseen Neighbors that explores themes with which members of our community have grappled historically, including race, difference, sexuality, and gender.

Within hours of the end of Roe, state abortion bans began to take effect and clinics began to close, leaving would-be patients with little time to lose scrambling to figure out where to go next in a shifting and unstable landscape. As stunning as this moment may be, it’s neither unprecedented nor unpredictable. We’ve seen changes in abortion access before, and economists have used data and statistics to study these “natural experiments”—situations where sudden localized change in access affords us an opportunity to isolate and measure causal effects. This type of quantitative research won’t tell the unique stories of women trying to figure out their next steps, but it can tell us something about their resolutions, providing a forecast of how many will likely ultimately reach a provider and how many, trapped by poverty and distance, will not find a way out.

Caitlin Knowles Myers is the John G. McCullough Professor of Economics and co-director of the Middlebury Initiative for Data and Digital Methods. Her research applies the statistical tools of causal inference to study the effects of abortion access on people’s lives. In addition to being published in scholarly outlets, her work also has been featured in the popular press such as The New York Times, Wall Street Journal, Washington Post, NPR, The Atlantic, and The New Yorker. She led an amicus brief sent to the Supreme Court in the Dobbs v. Jackson Women’s Health Organization case that was signed by more than 150 economists.