Voter Preferences and State Regulation of Smoking

Hersch, Joni; Rossi, Alison F. Del; Viscusi, W. Kip

doi:10.1093/ei/cbh073

Cited by 29 publications

(32 citation statements)

References 19 publications

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“…Regulations that restrict smoking in public areas may lower the costs to smokers of quitting by acting as a commitment device. As Hersch, Del Rossi, and Viscusi (2004) show, individual preferences over smoking restrictions map into government policy, as actual tobacco regulations within a state are consistent with preferences of voters within the state. 8 Such regulations once passed cannot be reversed if smokers find that regulations did not lower their costs of quitting.…”

Section: Introductionmentioning

confidence: 78%

“…Former smokers are less likely to support smoking bans than are never smokers, 12 As former smokers comprise only 23.8 percent of the entire sample, these quit plans probably wildly overstate the share that actually will quit successfully in this upcoming attempt. 13 These statistics are reported in Hersch, Del Rossi, and Viscusi (2004), Table 3. 14 Family income is reported in 14 ranges from the lowest category of less than $5,000 to the top category of more than $75,000.…”

Section: Datamentioning

confidence: 99%

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Smoking Restrictions as a Self-Control Mechanism

Hersch

2005

J Risk Uncertainty

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Using data from Current Population Survey Tobacco Use Supplements spanning 1992–2002, this study shows that smokers who plan to quit smoking are more supportive of regulations than are other smokers. Failed quitters who plan to try again are more supportive of restrictions than are smokers planning to quit for the first time. These findings indicate that many smokers support regulatory restrictions to reduce their costs of quitting by exploiting the discipline offered by regulatory control. From 1992 to 2002, support for smoking restrictions in public areas rose dramatically among both nonsmokers and smokers. Copyright Springer Science + Business Media, Inc. 2005time inconsistency, addiction, smoking restrictions, smoking cessation, cigarettes,

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Section: Introductionmentioning

confidence: 78%

Section: Datamentioning

confidence: 99%

Smoking Restrictions as a Self-Control Mechanism

Hersch

2005

J Risk Uncertainty

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“…16, 17, 20 Even after controlling for antismoking sentiment, there is still find evidence for the norm spreading effect of smokefree workplace and public place laws and evidence against “behavioral compensation.” Anti-smoking sentiment is highly correlated with the passage of the clean indoor air laws, therefore, the decreased association between smokefree laws and smokefree-home rules (OR = 7.76 without sentiment and OR = 4.08 with sentiment for full coverage and smoker households; OR = 4.12 without sentiment and OR = 2.44 with sentiment for full coverage and nonsmoker households) after controlling for antismoking sentiment may due to model over-adjustment (p < 0.01 without sentiment and p = 0.89 with sentiment for partial coverage and smoker households; p < 0.01 without sentiment and p = 0.99 with sentiment for partial coverage and nonsmoker households). The fact that there is a positive association between the presence of the laws and smokefree-home rules even after controlling for anti-smoking sentiment is consistent with the hypothesis that the existence of the law has a positive independent effect on smokefree-home rules.…”

Section: Discussionmentioning

confidence: 99%

Association Between Smokefree Laws and Voluntary Smokefree-Home Rules

Cheng¹,

Glantz²,

Lightwood³

2011

American Journal of Preventive Medicine

127

102

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Background More states and localities are passing restrictions on smoking in public places and workplaces. Purpose To determine what, if any, association exists between enactment of strong laws making public places or workplaces smokefree on adoption of voluntary smokefree-home policies, particularly whether such laws are associated with increased smoking at home. Methods Logistic regressions were used to quantify the OR of a person living with a 100% smokefree–home rule as a function of individual characteristics, household composition, and whether or not the residential region is covered by clean indoor air laws. The data came from successive waves of the Tobacco Use Supplement to Current Population Survey (TUS-CPS) for the years 1992–2007, and the American Nonsmokers’ Rights Foundation database of state and local government clean indoor air laws. Analysis was conducted in 2010 and 2011. Results Living in a county fully covered by a 100% clean indoor air law in workplaces or restaurants or bars is associated with an increased likelihood of having a voluntary 100% smokefree–home rule both for people living with smokers (OR=7.76; 95% CI=5.27, 11.43) and not living with smokers (OR=4.12; 95% CI=3.28, 5.16). Conclusions Strong clean indoor air laws are associated with large increases in voluntary smokefree-home policies both in the homes with and without smokers. These results support the hypothesis of norm spreading of clean indoor air laws.

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“…Extending the approach of Gilpin et al (2004) and Hersch et al (2004), our factor analysis is based on the idea that an unobserved latent variable (or common factor) is responsible for the correlation among the nine observed variables created from the TUS-CPS responses (Harman, 1976). In the spirit of using all available information, we pool data from the three cycles of the TUS-CPS and conduct the factor analysis on a sample of 616 796 observations.…”

Section: Measuring Anti-smoking Sentimentmentioning

confidence: 99%

Youth smoking, cigarette prices, and anti‐smoking sentiment

et al. 2007

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In this paper, we develop a new direct measure of state anti-smoking sentiment and merge it with micro-data on youth smoking in 1992 and 2000. The empirical results from the cross-sectional models show two consistent patterns: after controlling for differences in state anti-smoking sentiment, the price of cigarettes has a weak and statistically, insignificant influence on smoking participation, and state anti-smoking sentiment appears to have a potentially important influence on youth smoking participation. The cross-sectional results are corroborated by results from the discrete time hazard models of smoking initiation that include state-fixed effects. However, there is evidence of price-responsiveness in the conditional cigarette demand by youth and young adult smokers.

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Voter Preferences and State Regulation of Smoking

Cited by 29 publications

References 19 publications

Smoking Restrictions as a Self-Control Mechanism

Smoking Restrictions as a Self-Control Mechanism

Association Between Smokefree Laws and Voluntary Smokefree-Home Rules

Youth smoking, cigarette prices, and anti‐smoking sentiment

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