Abstract
Electronic cigarettes are a less harmful alternative to combustible cigarettes. We analyze data on e‐cigarette choices in an online experimental market. Our data and mixed logit model capture two sources of consumer optimization errors: overestimates of the relative risks of e‐cigarettes and present bias. Our novel data and policy analysis make three contributions. First, our predictions about e‐cigarette use under counterfactual policy scenarios provide new information about current regulatory tradeoffs. Second, we provide empirical evidence about the role consumer optimization errors play in tobacco product choices. Third, we contribute to behavioral welfare analysis of policies that address individual optimization errors. Compared with standard cost–benefit analysis, our behavioral welfare economics analysis leads to much larger estimates of the costs of policies that discourage e‐cigarette use or the benefits of policies that encourage e‐cigarette use.
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