Assist. Prof. Maria Polyakova, Ph.D.

Delegating Decision-Making to the Machine: Experimental Evidence from Health Insurance

Does delegating consumer decisions to algorithms affect consumer choices and market efficiency? Maria Polyakova and her collaborators conducted a randomised controlled trial in which they offered (elderly) consumers a decision-making support software for choosing among pharmaceutical insurance plans. They determined that algorithmic “expert” recommendation significantly alters consumer choices. At the same time, personalized, but passive, informational treatment had little effect on switching.

Ms Polyakova’s research interests are in health economics, public finance and the economics of regulation. Her work investigates questions surrounding the role of government in the design and financing of health insurance systems. She is interested in the design of subsidies in health insurance, individuals’ decision-making about health insurance plans and health care consumption, re-distributive properties of insurance, role of insurance in pharmaceutical markets and in long-term care.

Her current research projects include: 1) Social Insurance Design under Uncertainty: Evidence from Medicare’s Quantity Regulation (with David Chan) and 2) Social Insurance and the Labor Markets: Evidence from Long-Term Care (with Martin Hackmann).

Maria Polyakova is an Assistant Professor in the Department of Health Research and Policy at the Stanford University School of Medicine. She is an NBER Faculty Research Fellow, a Faculty Fellow of the Stanford Institute for Economic Policy Research (SIEPR) as well as a CESifo Research Network Affiliate. She holds a PhD in Economics from MIT and a BA in Economics & Mathematics and German Studies (History) from Yale University.