Impact of US smoke-free air laws on restaurants and bars by employer size: a panel study

Abstract

ObjectivesThirty states have smoke-free air laws that ban smoking in restaurants and bars, covering nearly two-thirds of the US population. It is well established that these laws generally have a null or positive economic impact on restaurants and bars. However, all establishments in a geographic area are usually treated as a homogeneous group without considering the potential for differential effects by establishment characteristics. This study uses variation in smoke-free air laws over time to estimate their impact on employment in restaurants and bars with a focus on potential differences by employer size (number of employees). A two-pronged approach with a national-level and state-level analysis is used to take advantage of more granular data availability for a single state (North Carolina).DesignObservational study using panel data.Setting1) US, 2) North CarolinaInterventionsSmoke-free air laws.Outcome measuresState-level accommodation and food services employment for all 50 states and District of Columbia from 1990 through 2014 (Quarterly Census of Employment and Wages); county-level restaurant and bar employment in North Carolina from 2001 through 2014 (North Carolina Department of Commerce).ResultsThere is no evidence of a redistributive effect of smoke-free air laws on restaurant and bar employment by employer size.ConclusionThe lack of a redistributive effect is an important finding for policy-makers considering implementation or expansion of a smoke-free air law to protect employees and patrons from the dangers of exposure to secondhand smoke.

The Impact of Restaurant Menu Calorie Labels on Restaurant Revenue and Profit: Evidence From a Randomized Controlled Trial

“…Our findings regarding the impact on restaurants contribute to the larger research literature on the effect of menu label laws, which historically has focused on consumer outcomes (e.g., Bollinger et al, 2011; Cantor et al, 2015; Cawley et al, 2020, 2021; Elbel et al, 2009; Finkelstein et al, 2011) or population body mass index (Courtemanche et al, 2020). More broadly, our results also contribute to the literature on the impact of legal regulations on the restaurant and hospitality industry (e.g., Dredge et al, 2016; Farmaki et al, 2015; Jin & Leslie, 2003; Johnson, 2018; Krutwaysho & Bramwell, 2010; Levin, 1964; Shafer, 2017; Siegel et al, 2005).…”

“…More broadly, this study contributes to the literature on the impact of legal regulations (such as smoking bans, liquor licensing, and hygiene inspections) on the restaurant and hospitality industry (e.g., Dearlove et al, 2002;Dredge et al, 2016;Enz et al, 1996;Farmaki et al, 2015;Jin & Leslie, 2003;Johnson, 2018;Krutwaysho & Bramwell, 2010;Levin, 1964;Shafer, 2017;Siegel et al, 2005).…”

Competing Public and Private Television Advertising Campaigns and Marketplace Enrollment for 2015 to 2018

“…In contrast, the volume of private ad airings was consistently large enough over time to split into separate Note: Crossover market refers to whether a county was potentially exposed to spillover advertising from a neighboring state-based marketplace by virtue of sharing a media market. We weighted our models by county population younger than sixty-five in 2017 (for the 2018 open enrollment period) to allow for more populous areas to be represented proportionally in our estimates as is often done in analyses of policy effects over many counties and/or states (Gertner, Rotter, and Shafer 2019;Shafer 2019Shafer , 2017. Standard errors were clustered at the state level to allow for correlation of errors across counties in the same state.…”