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Effects of Clean Indoor Air Laws on Bar andRestaurant Revenue in Minnesota Cities

Natalie M. Collins, MPH, Qun Shi, MS, Jean L. Forster, PhD,Darin J. Erickson, PhD, Traci L. Toomey, PhD

Background: In recent years, local governments have strengthened laws to prohibit smoking inbars and restaurants to promote patron and employee health. Because of concerns that clean indoorair policies could have negative economic effects on some hospitality businesses, some cities haveadopted partial clean indoor air policies (e.g., exempting bars).

Purpose: This paper considers how partial and comprehensive smokefree policies affected bar andrestaurant revenue, using quarterly data reported to the Minnesota Department of Revenue.

Methods: Data from ten Minnesota cities from 2003 to 2007 were used to conduct a time-seriesanalysis in 2009, adjusting for the population size of each city.

Results: Bars and restaurants governed by either partial or comprehensive policies had slightlyhigher revenues than those not regulated by any local clean indoor air policy. Bars and restaurantsgoverned by partial local bans reported 0.009% higher total revenue (p�0.5) and 0.052% higherliquor sales revenue (p�0.003) than those not covered by a ban. Bars and restaurants governed bycomprehensive local bans reported 0.026% higher total revenue (p�0.05) and 0.018% higher liquorsales revenue (p�0.35).

Conclusions: These fındings suggest that smoking bans, whether comprehensive or partial, do nothave a negative effect on bar and restaurant total or liquor revenues and may be associated withslightly higher revenue compared to not having a clean indoor air policy.(Am J Prev Med 2010;39(6S1):S10–S15) © 2010 American Journal of Preventive Medicine

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ackgroundn 1975, Minnesota became the fırst state to adoptclean indoor air legislation affecting private work-places, restricting smoking in order to protect public

ealth, comfort, and the environment.1 In recent years,ome county and municipal governments in Minnesotanacted more comprehensive policies to protect workersnd the public from secondhand smoke, which isnown to cause lung cancer, heart disease, respiratoryonditions, and other diseases in nonsmokers.2 In par-icular, these local ordinances sought to offer equal healthrotections to employees in bars and restaurants, work-laces that had only minimal restrictions in the 1975 statetatute (and subsequent amendments) on public smoking.Prohibiting smoking in workplaces is the most effec-

ive way to eliminate involuntary worksite exposure to

rom the Division of Epidemiology and Community Health, School ofublic Health, University of Minnesota, Minneapolis, MinnesotaAddress correspondence to: Jean L. Forster, PhD, 1300 South Second

treet, Suite 300, Minneapolis MN 55454. E-mail: forst001@umn.edu.

m0749-3797/$17.00doi: 10.1016/j.amepre.2010.09.011

10 Am J Prev Med 2010;39(6S1):S10–S15 © 2010 Amer

econdhand smoke.2 A review of studies of bar andestaurant employee exposure found that in establish-ents in which any smoking was allowed, levels ofecondhand smoke were 1.6 to 6.1 times higher thanhose found in other workplaces.3 Other studies haveound evidence that the physical health of bar andestaurant employees suffers when they are not pro-ected from secondhand smoke. In one study, non-moking workers in establishments where smokingas allowed had elevated levels of a tobacco-specifıcarcinogen in their urine, compared to those in smoke-ree establishments.4 In another study, bartenders’ re-piratory health improved from baseline after legisla-ion prohibiting smoking in bars and taverns wasnacted.5 Clean indoor air ordinances are a way toxtend health protections to all workplaces and end theisparity in harmful exposure for hospitality workers.Between 2000 and 2007, a total of 18 local governments

n Minnesota enacted clean indoor air policies that ex-eeded requirements of the state law and applied to hos-itality workplaces, although some of these policies

aintained an exemption for bars.6 These local policy

ican Journal of Preventive Medicine • Published by Elsevier Inc.

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hanges in Minnesota mirrored a national trend towardncluding hospitality employees in secondhand smokerotection. By 2009, over 400 cities in the U.S. had en-cted local, comprehensive clean indoor air policies thatncluded both bars and restaurants. Over 2000 cities hadnacted partial policies that exempted freestanding barsromworkplace smoking restrictions.7 The current studyxamines the effects of comprehensive bans, those en-orced in all indoor areas of all bars and restaurants; andartial bans, which apply only to restaurants.The persistence of exemptions for bars is based on the

stablished connection between alcohol consumptionnd smoking. People who are regular alcohol drinkersre more likely to be smokers than nondrinkers.8 Cleanndoor air policies make it more diffıcult to engage inne of these behaviors—smoking—in bars and restau-ants. Because of this, critics of clean indoor air ordi-ances assert that they may decrease alcohol sales, andaybe even food sales, if people who want to smokehile drinking no longer patronize bars after smokingans are implemented.A considerable and growing body of peer-reviewed

esearch has examined objective economic effects ofmoking bans, including revenue and employment inars and restaurants.9–23 Many of the studies on bar andestaurant revenue did not fınd any signifıcant effect ofmokefree ordinances, and some even detected positiveffects of increased revenue.9,12,15,21,23 One study of Cal-fornia restaurants found a small, temporary decline inevenue in alcohol-serving restaurants that quickly re-urned to normal levels.16 Recent literature has sug-ested consistency in fındings from different cities andegions.18–23

Despite this evidence, potential negative economic ef-ects continue to be an important part of the public debateround smokefree regulations for bars and restaurants.pponents of comprehensive smoking bans argue thatotentially increased expenditures by nonsmokers whoay be more willing to go to smokefree bars will notffset the loss of revenue in bars and restaurants result-ng from smokers choosing other ways to spend theireisure time. Research from California indicates thathe substitution effect of nonsmokers spending moreime and money in bars and restaurants after imple-entation of a clean indoor air policy is greater than

he effect of smokers choosing to stay away from barsnd restaurants.17 Nevertheless, when faced with theikelihood of smoking regulation, the tobacco industrynd hospitality trade groups have advocated for partiallean indoor air policies, exempting bars to reduceotential loss of revenue.This paper is designed to respond to those economic

oncerns, describing and comparing community-level p

ecember 2010

ffects of local clean indoor air ordinances on taxableevenue in bars and restaurants in a sample of Minnesotaities. A pooled time-series analysis was performed toetermine whether there were differences in taxable rev-nues in bars and restaurants among cities in which com-rehensive clean indoor air laws, partial laws exemptingome establishments, or no laws restricting smoking inars or restaurants were in place.This analysis is designed to add to our understand-

ng of the effects of clean indoor air policies in twomportant ways. First, it distinguishes among effects ofifferent types of clean indoor air laws (comprehen-ive, partial, and none) on bar and restaurant revenues.econd, this study directly compares clean indoor airolicy types using a pooled time-series design, whichnables modeling of variation in observations acrossoth time and communities.

ethodshis study examined economic effects of local clean indoor airrdinances, focusing on a time period duringwhich severalmunic-pal and county governments in Minnesota adopted or modifıedheir local ordinances regulating smoking in bars and restaurants,ut prior to the statewide comprehensive law.Because of the small number of localities with a local clean

ndoor air ordinance and the observational nature of the study, aonvenience sample of Minnesota cities was used. Initially, all fıveinnesota cities with a complete ban on smoking in bars and

estaurants for some or all of the study period and with a substan-ial number of bars and restaurants were selected. All of these citiesre located in the seven-county Twin Cities metropolitan area.ities of comparable size were then selected with an exemption forars and with no restaurant or bar policy (Figure 1).The sample included eight cities that had local clean indoor airolicies (partial and/or complete bans) during some quarters of thetudy period and two comparison cities without any local regula-ion of smoking in bars or restaurants during the study period. Noomparison city without a ban of the size of Minneapolis and St.aul was available. To protect the confıdential information of busi-esses in smaller cities, only Minneapolis and St. Paul aredentifıed.All partial bans included exemptions for bars, generally defıned

s establishments that draw more than 50% of their revenue fromlcohol sales.Data on taxable revenues were obtained from the Minnesotaepartment of Revenue (MN Revenue), which collects this infor-ation directly from businesses in their quarterly tax returns.evenue amounts reported by MN Revenue and included in thisnalysis are sales receipts, not the amount of tax collected. Revenuemounts for bars and restaurants were aggregated to the city levelor each quarter.Revenue data were obtained for “full-service restaurants” and

drinking places” as defıned by the North American Industry Clas-ifıcation System (NAICS) industry codes 7221 and 7224. NAICSodes are self-reported by businesses as they fıle tax returns withhe state. In accordance with their internal policies and in order to

rotect the confıdentiality of individual business owners, MNRev-

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nue does not release informa-ion in any category thatould contain fewer than tenusinesses reporting sales taxata. For some of the cities inhis study, fewer than ten busi-esses in either NAICS code221 or code 7224 reportedevenue in some quarters. Be-ause someof the cities did notave ten businesses in at leastne category during at leastne quarter, MN Revenue col-apsed the NAICS categories,nd revenue numbers for full-ervice restaurants and barsere reported together as oneumber. Thus it was not pos-ible to evaluate the effects oflean indoor air ordinances onevenue for bars and restau-ants separately. Taxable reve-ue amounts were reportedeparately for sales of alcoholreported as “liquor” revenue)nd for general sales, as well astotal combined revenue forll products.Revenue data for bars and restaurants in the ten cities were

athered for January 2003 through September 2007, equaling 19uarterly time points per community. This time interval was cho-en because on October 1, 2007, a comprehensive statewide cleanndoor air policy was implemented, superceding most local gover-ance of smoking in bars and restaurants.The primary outcome measures of this study were total taxable

ales (or total revenues) and liquor taxable sales (or liquor reve-ues), and the primary explanatory variable was clean indoor airrdinance type, defıned with three levels: comprehensive, partial,nd none. To account for revenue change differences due to pop-lation, the community population size, based on Census 2000,as included as a covariate.24

The primary research question was whether the level of cleanndoor air ordinance is associated with bar and restaurant revenueeither total or alcohol-specifıc). First, a visual inspection of theerial data was conducted by plotting the dependent variables overime. Plots for each of the dependent variables (total taxable salesnd liquor taxable sales) were represented with various policyypes. The plots give an initial impression of the data, such asresence or absence of change, cyclical patterns, and trends.The second analytic step was regression of each dependent vari-

ble on policy. Because data for each community are longitudinalnd revenues at adjacent quarters are likely correlated, regressionodels must account for this non-independence to produce unbi-sed estimates of the SEs associated with the clean indoor air policyredictors. Box–Jenkins autoregressive integrated moving averageARIMA) models, often used to analyze this type of data, wouldequire separate models for each of the ten cities and would benderpowered given only 19 time points.Alternatively, pooled time-series analysis allows combined analysis

Figure 1. Clean indoorSource: Minnesota Depart

f cross-sectional units (in this case, ten Minnesota cities) with i

emporal units (in this case, 19 quarters) by policy condition. Theotal sample size is determined by multiplying the number of citiesy the number of time points, for a total of 190 observations. All ofhe revenue data from city-quarters duringwhich a comprehensivelean indoor air policy was in place are combined into one pool ofata, as are all of the city-quarters where there was a partial smok-ng ban, and all of the city-quarters where there was no smokingan in bars or restaurants. Units in each pool are drawn from citiesndquarters across the study pool andperiod based on the policy inffect at that time and place. Pooled time-series cross-sectionalegression models allow for comparisons both across time andmong cities, while accounting for correlation in the errors androviding unbiased SEs.Models were estimated using PROC TSCSREG (SAS, version

.1.3). After a comparison of the available error structures, thearksmethodwas chosen based on appropriateness for generalizedeast-squares regression and generating the largest model-square. Models provided estimates of the percentage change inevenue (with p-value) associated with different levels of cleanndoor air ordinance after adjusting for community populationize.

esultsotal revenues (total taxable sales) for bars and full-ser-ice restaurants in each of the ten cities are shown inigure 2. Each line in this fıgure represents a community’snadjusted quarterly revenue amount, with the line styleeflecting the types of clean indoor air laws in place overime. Quarterly liquor revenues are similarly represented

ordinance status by quarter by city, 2003–2007t of Revenue

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To evaluate whether implementation of clean in-oor air ordinances changes the relative levels of liquornd food sales, an examination was also made of theroportion of liquor sales within total bar and restaurantales in each of the ten cities. The proportion of alcoholales within total bar and restaurant sales ranged from0% to 30%, with a slight secular trend toward a greaterroportion of alcohol sales over the study period regard-ess of policy type, and with seasonal trends suggested inany cities.Results of the pooled time-series analysis indicated

hat after adjusting for population, bars and restaurantsn city-quarters with either type of clean indoor air ordi-ance had slightly higher revenues than those with nolean indoor air law beyond state law (Table 1). Bars andestaurants in city-quarters with partial local bans re-orted 0.009% higher total revenue (p�0.5) and 0.052%igher liquor sales revenue (p�0.003) than those in city-uarters with no ban. Bars and restaurants in city-uarters with comprehensive local bans reported.026% higher total revenue (p�0.05) and 0.018%igher liquor sales revenue (p�0.35) compared to

igure 2. Total taxable revenue in bars and restauran003–2007

hose with partial or no ban. a

ecember 2010

DiscussionFindings from this studysuggest that local cleanindoor air ordinances,whether comprehensiveor partial, had no ad-verse effects on bar andrestaurant revenue incities in Minnesota. Cit-ies with either type ofclean indoor air law(comprehensive or par-tial) showed higher reve-nue from both liquorand total sales comparedto cities with no clean in-door air ordinance. Pre-vious studies from Mas-sachusetts and New YorkCity found that smokingrestrictions had positive,but nonsignifıcant, effectson bar and restaurant reve-nue.15,21 An analysis of barand restaurant revenue inCalifornia showed signifı-cant associations between astate-level ban on smokingin restaurants and a mi-

or increase in restaurant revenue, and a state-level com-rehensive smoking ban and an increase in bar revenue.17

recent evaluation of the smoking ban in Pueblo CO,howed a slight decrease in tax revenue for taverns morehan offset by a signifıcant increase for restaurants.23 Inhe present study, fındings suggest not only that cleanndoor air policies have positive effects on revenue, butlso that these effects were sometimes signifıcant.While positive, the magnitude of the effects in revenueas small. Anecdotal evidence offered during public tes-imony for and against the local smoking bans in Minne-ota often indicated that bars and restaurants operate onlim margins, so even a small difference in revenues mayean the difference between an establishment maintain-

ng operations or going out of business. Contrary to con-erns that such ordinances will decrease revenue, enact-ent of a clean indoor air ordinance appears to improve

he profıt margin of bars and restaurants overall ratherhan detract from it.This study is one of the fırst to examine the economic

ffects of different levels of clean indoor air ordinancesimultaneously, through the use of pooled time-series

or ten Minnesota cities,

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nalysis. Our fındings are consistent with a previous

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tudy using this design tonalyze employment datan Minnesota.18

A strength of this studyas the use of objectiveata gathered by a stateovernment agency forultiple purposes, pri-arily tax collection, andlso other types of re-earch rather than infor-al, self-reported data.Another strength of

he study was the use ofooled time-series cross-ectional analysis, whichnabled comparison ofolicy conditions acrossyears by quarter and

mong ten cities. Whileooled time-series analy-is provides several benefıtsn this study, it does requiressumptions about theimilarities among cities ineneral economic condi-ions, policy effects, andompliance with the cleanndoor air policies.A potential limitationf this study is that while data obtained for this analysisere consistently collected by and reported by MN Rev-nue, theremay be inaccuracies in industry classifıcation.AICS codes are defıned by the federal government, andhe Census Bureau offers an interactive online guide toetermining NAICS code. However, there is no offıciallyssigned code for any particular business. Businesses re-orting revenue to the state of Minnesota assign them-elves to a NAICS code, and there is limited oversight oreview to ensure that establishments are accuratelylassifıed.Another potential limitation is that temporal events be-

ond the change in clean indoor air ordinances may beesponsible for the fındings, although such other temporalvents would have toave different impactsn cities that did or didot adopt clean indoorir ordinances.The level of analysisossible with communi-y-level revenuedata also

Figure 3. Liquor taxable2003–2007

Table 1. Percentage differenclean indoor air policy type

Type of cleanindoor air ordinance

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imits this study. Because Partial �0

f the need to protect individual business information, itas not possible to examine effects of clean indoor airrdinances on individual establishments, on bars versusestaurants, or at smaller geographic levels. The observedooled effects should not be taken to describe the experi-nce of any particular business.

onclusionhe results of this study suggest that neither comprehen-ive nor partial smoking bans adversely affect the eco-omic success of bars and restaurants as an industry anday be associated with slight increases in revenue. Thatomprehensive smoking bans appear to offer no negativeffect to theeconomic successofbars andrestaurants, and in

nue in bars and restaurants for ten Minnesota cities,

n total and liquor revenue in bars and restaurants by

enue vs nonce (%) p-value

Liquor revenue vs noordinance (%) p-value

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act, may slightly increase revenues, only adds to theirppeal.

his work was supported by grant RC-2006-0047 from Clear-ay Minnesota. The contents of this manuscript are solely the

esponsibility of the authors and do not necessarily reflect theffıcial views of ClearWay Minnesota.The authors acknowledge the assistance of staff in the Taxesearch Division of the Minnesota Department of Revenue inetrieving and assembling the data.No fınancial disclosures were reported by the authors of thisaper.This paper was supported by ClearWayMinnesotaSM as partf a supplement entitled ClearWay MinnesotaSM: Advancingobacco Control Through Applied Research (Am J Prev Med010;39[6S1]).

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