A Dynamic Model of Rational Addiction with Stockpiling and Learning: An Empirical Examination of E-cigarettes

• 成果类型: Article
• 署名作者: Chen, Jialie; Rao, Vithala R.
• 署名单位: University of Arkansas System; University of Arkansas Fayetteville; Cornell University
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.2019.3490
• 发表日期: 2020
• 关键词: dynamic structural model; learning; e-cigarettes; rational addiction; POLICY IMPLICATIONS

摘要

Current regulations on e-cigarettes are minimal compared with cigarette regulations, despite their growing popularity globally. Advocates of e-cigarettes claim that they aid in ceasing smoking habits. However, leaving e-cigarettes unregulated has raised growing health concerns. Policymakers in several countries, including the United States and those in Europe, are considering and experimenting with policy interventions. To evaluate current policies and implement potential regulations on e-cigarettes, policy makers must understand the impact of e-cigarettes on consumers' smoking behaviors. To address this issue, we construct a dynamic structural model that incorporates consumers' purchases and consumption behaviors of both cigarettes and e-cigarettes. The results from our proposed model indicate that consumption of e-cigarettes promotes, rather than counteracts, smoking. This is because the less costly e-cigarettes incentivize consumers to build their addiction to nicotine, which, in return, increases future consumption of both cigarettes and e-cigarettes. This finding calls for regulations on e-cigarettes. We then conduct counterfactual analyses to evaluate two policy regulations on e-cigarettes: (1) e-cigarette taxes and (2) price regulation. Because both of these policies have been discussed extensively in both the United States and many countries in the European Union, results of our policy simulations address these policy debates. We find that both are effective in reducing overall consumption of cigarettes and e-cigarettes. We also examine the role of consumers' heterogeneity on the simulation results as well as the policy implications. We conclude with future research directions, such as inclusion of social influence and cross-selling marketing.