Trade-offs of simplifying complex choices: early evidence from the ACA Exchanges

Using new data from the early years of the federally-facilitated Health Insurance Marketplaces (or ACA Exchanges), we explore which factors affect the health insurance choices of the non-elderly population targeted by the ACA. A growing literature has documented potential behavioral biases and high cost of decision-making in various insurance settings that rely on consumer choice - from retirement savings to prescription drug plans. A natural conclusion from this literature is that it may be optimal for policy-makers to introduce behavioral nudges (e.g. optimal defaults, framing) that could reduce the behavioral biases or decision-making costs. For example, ACA Exchanges use "metal level" classification of plans as a framing that reduces the complexity of comparisons across dozens of plans on the Exchanges. So far, we have little evidence on how such nudges work in practice, and whether they are strictly welfare-improving or may lead to unintended consequences. In this project we attempt to start closing this gap by exploring whether the metal tier framing affects choices in the federally facilitated Health Insurance Marketplaces.