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Mostly Harmless Regulation? Electronic Cigarettes, Public Policy and Consumer Welfare

Author: Donald S Kenkel; Sida Peng; Michael F Pesko; Hua Wang; National Bureau of Economic Research.
Publisher: Cambridge, Mass. National Bureau of Economic Research 2017.
Series: Working paper series (National Bureau of Economic Research), no. w23710.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
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: over-estimates 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  Read more...
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Details

Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Donald S Kenkel; Sida Peng; Michael F Pesko; Hua Wang; National Bureau of Economic Research.
OCLC Number: 1008873891
Notes: August 2017.
Description: 1 online resource
Series Title: Working paper series (National Bureau of Economic Research), no. w23710.
Responsibility: Donald S. Kenkel, Sida Peng, Michael F. Pesko, Hua Wang.

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: over-estimates 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 counter-factual 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.

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