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Journal of Health Economics
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educing underage alcohol and tobacco use: Evidence from the introductionf vertical identification cards
ndriana Belloua,∗,1, Rachana Bhattb,2
Departement of Economics and CIREQ, Université de Montréal, C.P. 6128, succursale Centre-ville, Montréal, QC H3C 3J7, CanadaDepartment of Economics, Andrew Young School of Policy Studies, Georgia State University, P.O. Box 3992, Atlanta, GA 30302-3992, United States
r t i c l e i n f o
rticle history:eceived 22 June 2012eceived in revised form1 November 2012ccepted 3 December 2012vailable online 22 December 2012
a b s t r a c t
From 1994 to 2009, forty-three states changed the design of their driver’s license/state identification cardsin an effort to reduce underage access to and consumption of alcohol and tobacco. In these states, individ-uals under the age of 21 are issued licenses that are vertically oriented, whereas licenses for individuals21 and older retain a traditional horizontal shape. This paper examines the effect of this design changeon underage alcohol and tobacco use. Using a difference-in-differences methodology, we find a reduction
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in drinking and smoking for 16 year olds. These results are upheld in a triple difference model that usesa within state control group of teens that did not receive a vertical license to control for state-specificunobserved factors. Interestingly, we find that the effects of the design change are concentrated in the1–2 years after a state begins issuing vertical licenses. We consider various explanations for our findings:teen learning, the availability of false identification, and changes in retailer behavior.
To combat these illegal sales, several states have redesigned
outh alcohol and tobacco policies
“Employing the use of differently-shaped driver’s licenses for thoseboth under and over the age of 21 would make it easier to quicklyestablish a person’s legal age. . .. The legislation would also bean effective tool in combating the sale of alcohol and tobacco tominors”New York State Senate Bill 929–2011, 2011.
. Introduction
Tobacco and alcohol use by teens and adolescents is a promi-ent public health issue. Research has linked tobacco use to
ncreased rates of lung cancer and asthma (U.S. Department ofealth and Human Services, 2001), and alcohol use to a number ofdverse outcomes such as crime (Carpenter, 2005; Carpenter andobkin, 2010), risky sexual behavior (Waddell, 2012), unemploy-ent (Renna, 2008a; Mullahy and Sindelar, 1996), poor academic
erformance (Renna, 2008b; Carrell et al., 2011), and traffic fatal-
ties (Grant, 2010; Dee, 1999). The medical and social costs ofreating drinking and smoking related illnesses are estimated toe in the billions (Miller et al., 2006; CDC, 2008).
Since the early 1990s, it has been illegal for individuals in alltates to purchase tobacco or alcohol until the ages of 18 and 21,espectively.3 While no systematic data exists on the number ofllegal sales, two interesting patterns emerge from survey data andsting” compliance checks wherein law enforcement officials sendnderage youth into retail stores to purchase alcohol or tobacco.irst, retailers often ignore age requirements: close to 50% of retail-rs that failed compliance checks in 2009 did not ask for prooff identification, and in 30% of cases, they asked for identificationut made the sale anyway. Ex-post, retailers claim they were toousy to check for identification, or that they miscalculated con-umer’s age (We Card, 2009). Second, teens use false identificationnd are knowledgeable about which retailers do not check for iden-ification: 65% of teen smokers from 1995 to 2005 reported buyingobacco without proof of id, and Lee et al. (2011) find that 10% ofeen drinkers and smokers use false identification.4
heir driver’s license and identification cards to have a vertical (i.e.,ortrait) orientation for individuals under 21, while those 21 and
3 During the 1970s and 1980s every state increased their minimum drinking ageo 21 to avoid losing federal highway funds (Dee, 1999). Similarly, all states estab-ished a minimum smoking age of 18 by 1994 to prevent loss of Federal Emergency
anagement Agency funds (American Lung Association, 2010).4 This figure is based on the authors’ calculations using data from the Youth Riskehavior Surveillance System.
tstcmrthat reported buying directly from retailers were asked whetheror not the seller requested to see their identification (availablefrom 1995 to 2005). Fig. 1 documents the percentage of teens that
54 A. Bellou, R. Bhatt / Journal of H
bove have a horizontal (i.e., landscape) card. The logic behind thehange is twofold: first, the vertical design is intended to maket easier/less costly (in terms of time and effort) for a retailer todentify someone’s age. Perhaps more importantly, the redesignliminates the credibility of retailers to claim human error after aale. Second, it would not be effective for youth to tamper with thege on their license since the orientation reveals this information.
This paper examines the effect(s) of the vertical design onnderage consumption of tobacco and alcohol. Although the ver-ical design has been touted as a low-cost, effective method ofeducing underage sales, a priori, it is not clear whether thehange has had a meaningful effect on consumption.5 For instance,hile the vertical license may prevent teens from using their
wn identification to purchase tobacco and alcohol from retailers,onsumption may not decrease if teens substitute toward otherethods of obtaining these products. Moreover, retailers may con-
inue to disregard age requirements, simply for profit motivations.To examine the impact of the design change, we use data on
eens from the Youth Risk Behavior Surveillance System (YRBSS)long with information on whether, and in which year, states beganssuing vertical licenses. We use a difference-in-differences modelhat exploits variation across time in the years that states switchedo the vertical design. The results indicate that the vertical licenses associated with a significant reduction in the probability that6 year olds smoke or drink by 8–10%. There is no effect for 17–18ear olds. These results are upheld in a triple differences model thatses a within state control group of teens that did not receive theertical license. Due to the potential for misclassification in whicheens have a vertical license, these estimates should be interpreteds lower bounds of the effects of the license redesign.
One of our most interesting findings is that the effects of the newolicy are concentrated in the short run: the vertical design reducesonsumption of 16 year olds the most in the 1–2 years after a statewitches to the new design, whereas subsequently, the effects aremall, negative, and statistically insignificant. To better understandhese results, we examine data on tobacco transactions and sources.
e find suggestive evidence that over time teens substitute towardther methods of obtaining tobacco as they gain more “experience”ith the vertical license, and this could include an increase in these of false identification cards. There is little evidence of changes
n retailer behavior.The remainder of this paper proceeds as follows: Section 2
eviews the literature and discusses the data. Section 3 outlineshe empirical approach, and Section 4 details the results. Section 5rovides a discussion and Section 6 concludes.
. Related literature and data
.1. Related literature
This paper contributes to the literature on state policies thatre aimed at curbing youth tobacco and alcohol use. Some poli-ies target the sources that teens obtain alcohol and tobacco fromhile others affect the demand for these products. With respect
o alcohol, Dills (2010) examines the impact of social host lawshat target third party involvement by holding adults liable for
roviding alcohol to minors, and finds that the laws do not reduceeports of underage drinking but do reduce drunk-driving fatalities.arpenter (2004) examines the impact of zero tolerance laws which
5 After Michigan adopted vertical licenses, then Secretary of State Terri Lynn Landemarked “The vertical ID program is doing its part to help teens avoid the enormousisks that come from alcohol and tobacco use”(State of Michigan, 2008). To the bestf our knowledge, no rigorous statistics have been published to support such claims.
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Fig. 1. Youth tobacco and alcohol use in past month.
et the legal blood alcohol content limit for minors at low levels andnds reductions in heavy drinking for males but no effect on self-eported drunk driving. Grant (2010) finds no evidence that zeroolerance laws reduce traffic fatalities. Dee (1999) examines thempact of beer taxes and increasing minimum legal drinking agesnd finds the former has no effect, while the latter are associatedith decreased consumption.
Numerous studies have examined the responsiveness of youthobacco demand to price, with mixed results. While some find
decrease in demand when price increases (Lewit et al., 1981;rossman et al., 1983; Evans and Farrelly, 1998; Carpenter andook, 2008; Chaloupka and Wechsler, 1997), others find no effectDeCicca et al., 2002). Chaloupka and Grossman (1996) examinehe effect of tobacco policies such as restrictions on the location ofigarette vending machines. The authors find inconsistent effectscross specifications and conclude that these policies have littlempact due to lack of enforcement by states.6
.2. Data
The analysis draws on data from a number of sources. We useata from the national Youth Risk Behavior Surveillance SystemYRBSS), which is a biennial, cross-sectional survey spanning theears 1991–2009. Each survey year, high school students (ages2–18) are surveyed, and information on their demographic char-cteristics, state of residence, and drug, alcohol and tobacco use isollected.7 For our analysis, we pool data from all survey years andimit the sample to 16–18 year olds since these teens are the mostikely to hold driver’s/state identification cards (we elaborate moren this in Section 3).
In every survey year each teen is asked about the frequencyhat he/she used alcohol and tobacco in the month prior to theurvey. This includes the number of days in the past month thathe individual smoked, drank, chewed tobacco, the number ofigarettes consumed per day, and the number of days when 5 orore drinks were consumed. In the years 1995–2009, teens who
eported smoking were asked how they obtained tobacco. Those
6 Our analysis controls for various state policies aimed at reducing teen alcoholnd tobacco use.7 The YRBSS is administered by the Center for Disease Control (CDC). State of res-
dence is obtained from the restricted-use version of the YRBSS which is availablerom the CDC upon request. The survey is designed to be nationally representativethis is achieved using survey weights), however not all states were asked to partic-pate in every year. Appendix Table 1 documents the participation history for eachtate from 1991 to 2009.
eported drinking or smoking at least once in the prior month overhe last two decades. Although rates of use have declined over time,009 levels (19.5% for smoking and 41.8% for drinking) are still high.
We supplement the YRBSS sample with data on the year eachtate adopted a vertical license, state-level demographic character-stics, and a series of other state policies used to reduce underagerinking and smoking. Appendix Table A.1 lists the year each ofhe adopting states first issued a vertical license. The first stateas Colorado in 1994, and by 2009 (the end of our YRBSS sam-le) only 8 states did not have vertical licenses. Fig. 2 displays theapid increase in states’ adoption of the vertical design, particularlyfter 2001.8
The state level demographic information includes medianousehold income and unemployment rate. In addition, we col-
ect data on (real) cigarette and beer taxes, as well as the years inhich each state enacted laws and policies that could affect youth
onsumption. These include: a social host law, a graduated driver’sicense law (which affects unsupervised driving), a zero toleranceaw, a minimum legal smoking age of 18, a ban on smoking in publiclaces, restrictions on the placement of cigarette vending machinesnd cigarettes, a policy requiring all customers to show identifica-ion, and the year each state issued punishments to minors whory to purchase tobacco.9 These covariates were selected based on
heir potential relevance for influencing underage consumption,nd their use in prior studies (Dills, 2010; Dee, 1999; Carpenternd Cook, 2008; Chaloupka and Grossman, 1996).10
8 We obtain this information from official state press releases, Depart-ent/Bureau of Motor Vehicles and State Department of Transportation
afety/Public Safety websites, and direct contact with state administrators. We refero the year that a state first prints and issues vertical licenses as the “year of ver-ical license adoption” or the year a state “went vertical”. This may differ from theear that a state passed legislation approving the design change. We were unableo determine the exact month that vertical licenses were first issued.
9 The year a state began punishing minors for underage tobacco purchases referso the year there is a punishment on record in state legislature (American Lungssociation, 2011). We do not include the year states began punishing tobacco retail-rs for illegal sales because there are only three states that did not punish retailersrior to 1991. That said, results controlling for seller punishment are qualitativelyimilar, and available upon request. We were not able to locate data on the yearstates began to punish buyers and sellers for illegal alcohol transactions. Althoughhis is a limitation of our analysis, it is likely that punishment for alcohol violationsained popularity during the 1970s and 1980s when states were making changes tohe minimum legal drinking age. Finally, we do not include a control for a minimumegal drinking age since every state had a minimum age of 21 prior to 1991.10 Data on income and unemployment were obtained from the U.S. Census. Datan state tobacco and alcohol policies were obtained from a variety of sources:i) Graduated Driver’s License: Dee et al. (2005) provides information until 2002nd the remaining years were updated using the IIHS (2011), (ii) Zero Tolerance:HTSA, (iii) Social Host: Dills (2010) provides information until 2005 and the
emaining years were updated using APIS (2011), (iv) Ban on smoking in public loca-ions: American Nonsmokers’ Rights Foundation (2011), (v) Real Beer and Cigarette
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Economics 32 (2013) 353– 366 355
We also compile state level data on retailer violation rates dur-ng “sting” tobacco compliance checks. In 1992, the U.S. Congressassed the Synar Amendment, which tasked states with develop-
ng policies to reduce youth access to tobacco. The Amendmentequired states to conduct yearly random compliance checks start-ng in 1997, document the rate of violations, and develop yearlyargets. For each state and year from 1997 to 2009 we observe theercent of retailers who failed these checks and their target rates.11
e utilize this data to examine how the redesign affected retaileriolations. Note that because the Synar Amendment encouragedtates to adopt policies to combat underage access, it is importanthat we control for other state policies, such as restrictions on thelacement of cigarette vending machines, in the analysis.
Finally, we use state-level data on traffic fatalities to evaluatehether the vertical license had any auxiliary effects (through alco-ol consumption) on the number of fatal car accidents involvingeens. The data is drawn from the Fatality Analysis Reporting Sys-em (FARS) Encyclopedia of the National Highway Traffic Safetydministration (NHTSA). For each year from 1994 to 2009, webserve the number of drivers of a given age that were involvedn a fatal car crash, the time of the crash, and the state where theriver’s license was issued.
. Empirical framework
.1. Difference-in-differences model
To examine the impact of the design change we estimate theollowing difference-in-differences (DD) model:
ist = ˇ0 + ˇ1 Verticalst + ˇ2Xist + ˇ3Zst + ss + tt + εist (1)
ere Yist denotes the tobacco or alcohol use of teen i in state s andear t. We define five binary outcomes following the previous liter-ture (Carpenter and Cook, 2008; Carpenter, 2004): (i) smoke: equalo one if a teen smoked at least one cigarette in the month prior tohe survey, (ii) smoke frequently: equal to one if a teen smoked ateast 20 days in the past month, (iii) chewing tobacco: equal to onef a teen used chewing tobacco in the past month, (iv) drink: equalo one if a teen drank at least one alcoholic drink in the past month,nd (v) binge drink: equal to one if a teen drank at least 5 drinks inne sitting in the past month.12
Xist is a vector of demographic characteristics of student i thatncludes grade level, sex, and race. Zst is a vector of state level vari-bles including unemployment, median family income, real beernd cigarette taxes, and the various state policies on tobacco andlcohol access described in Section 2.2. Each of these policies isormulated as a binary variable equal to one for the states andears that the laws were in effect, and zero otherwise. ss and tt aretate and year fixed effects; the former captures any time invariant,tate specific factors which may influence teen behavior, and theear fixed effects capture any factors that are common to all statesithin a given year. Verticalst is the policy variable of interest, and
s formulated as a binary indicator that equals to one for teens thateceived a vertical driver’s license.13 We identify the impact of theicense from within state changes in teen outcomes that result from
axes (in 1984 dollars): Beer Institute (2011) and Orzechowski and Walker (2010),vi) All remaining tobacco restrictions: American Lung Association (various years;990–2010).11 Data on retailer violations rates were obtained from the Substance Abuse andental Health Services Administration (SAMSHA).
12 The intensity variables Smoke Frequently and Binge Drink are measured for indi-iduals that reported they smoked or drank at least once in the month prior to theurvey.13 We do not index Verticalst by i since we estimate Eq. (1) separately by age group.
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56 A. Bellou, R. Bhatt / Journal of H
he switch in a particular year (treated), relative to the within statehanges in outcomes for teens in states where a vertical licenseas not adopted in that same year or was never adopted (control).e use sampling weights from the YRBSS, cluster standard errors
t the state level, and estimate cluster-robust standard errors toddress issues of serial correlation following Bertrand et al. (2004).
The structure of the data requires us to make a series of assump-ions in order to construct Verticalst. In particular, the YRBSS doesot include information on whether an individual has a driver’s
icense/state identification card. As a starting point, we restricthe sample to 16–18 year olds, assume all these teens hold ariver’s/state license, and that all teens receive a license startingt age 16. This is based on the fact that in most states during ourample period, teens gained driving privileges starting at 16. Thataid, in Section 5 we discuss how our results would change if not alleens had a license, and if teens first receive a license at age 15.14
When states began to issue vertical licenses, this only affectedesidents who obtained their license for the first time. Those under1 that already had a license were not required to obtain a newvertical) one. We do not observe the exact date that a state beganssuing vertical licenses, nor teens’ date of birth.15 Consequently,
e make the simplifying assumption that the vertical licenses wererst issued on January 1 of the year of the switch, and that any6 year olds observed in that year turned 16 after January 1, andhus hold a vertical license. Further, we assume any 16 year oldsbserved after that year turned 16 after the change. As a result, if
state switched designs in 2005, we classify all the 16 year olds inhat state in 2005 and subsequently as having a vertical license, andll 16 year olds prior to 2005 in that state as not having a verticalicense. Following the same logic, we classify 17 year olds one yearfter their state went vertical and 18 year olds two years after asolding a vertical license. In the 2005 example, 17 (18) year olds in007 (2008) and after are classified as having the license. That is,e assume these teens received their license at 16, and turned this
ge after their state went vertical.It is important to note that when we observe 17–18 year olds,
hey have already held a license for 1–2 years. As a result, they mayave more experience with it than 16 year olds. Experience maye important; a 17–18 year old that received a vertical license at6 may have discovered ways to “get around” the restrictions ofolding the redesigned license (i.e., asking an older adult to makeurchases on their behalf). Moreover, because the design changeas coupled with other changes to licenses that made them harder
o forge (we describe this in detail below), this might have made itarder to obtain a fake identification card immediately after theesign change, but over time (say 1–2 years after the redesign,hen a teen is 17–18 year olds), the supply of fake cards could
ave caught up with demand. To this end, we conduct our analysiseparately by age.
14 We define the age when an individual gains driving privileges as the age theyan drive without adult supervision. During our sample period, the majority of stateshifted to a graduated driver’s license system that is composed of three levels: (i)earner: individuals can only train with licensed drivers, (ii) intermediate: unsuper-ised driving is permitted, but only during the day, (iii) full privileges: no restrictionsIIHS, 2011). For most states and years in our sample, teens reach the “Learner” staget age 14 or 15 (in some states it is as late as age 16), and the “Intermediate” level atge 16 (there are a handful of states (prior to 1995) where teens reach this stage byge). We reason that teens are most likely to be issued state licenses once they canrive unsupervised. Prior to that they likely only carry a permit. That said, if teensold a license during the “Learner” stage, or if some teens reach the “Intermediate”tage at age 15, then our analysis in Section 5, where we assume teens receive aicense at 15, will address this.15 All YRBSS surveys took place in the spring (February–May), but the exact inter-iew date is not known.
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Economics 32 (2013) 353– 366
Our classification of which teens have a (vertical) license willntroduce measurement error in four ways. First, we assume alleens hold a driver’s license/state identification card. Second, wessume teens first obtain a license at age 16, whereas some maybtain it at 15. Third, we assume that all teens observed in theear their state went vertical turned their current age after thehange. Fourth, we assume all teens that were issued a licenseefore their state switched designs continue to hold a horizon-al license, even though some may have obtained a new (vertical)icense (say, to replace a lost card). In Section 5, we conduct a seriesf sensitivity analyses to examine the role of measurement error.verwhelmingly, these analyses indicate that measurement erroroes not substantively drive our findings. That said, any misclas-ification will attenuate the estimates, and thus our results shoulde interpreted as a lower bound.
.2. Policy endogeneity, short and long run effects
The identifying assumption for the DD model is that the con-rol observations act as a valid comparison group for the treatedbservations. This will not hold, if for instance, states that werelready experiencing reductions in underage consumption wereore likely to adopt the design change in a given year. If this
s the case, then the estimated effects will simply reflect a con-inuation of this pre-existing trend. A related concern is policyndogeneity. There may be unobserved state characteristics (i.e.,ttitudes toward public health) which drive the decision to makehe design switch, and which are correlated with underage con-umption. While we attempt to address these issues to the bestf our ability in the model below, we first provide three pieces ofnecdotal and graphical evidence regarding states’ adoption of theew design.
First, for many states, the timing of the design change coincidesith the end of states’ multi-year contracts with license card manu-
acturers. Presumably states waited until this point in order to avoidncurring costs associated with modifying contracts. In conversa-ions between the authors and one of the largest manufacturers oficenses, it was determined that any changes to the license designhat occurs mid-contract would come at a cost of up to a few thou-and dollars.16 As a result, the exact timing of the design change isikely to be uncorrelated with unobserved state heterogeneity. Sec-nd, after September 2001, states were urged at the federal level todopt new security changes for licenses which would make themarder to forge, such as the use of barcodes, holograms, and design
eatures like the vertical orientation. This is reflected in the rapidncrease in vertical licenses post-2001. This suggests that one moti-ation for the redesign was common across many states, ratherhan driven by state-specific factors.17
Third, trends in underage consumption are largely similar acrosstates that adopted the vertical license and those that did not, prioro adoption. These trends are graphed in Fig. 3, where the solidines reflect the average percentage of 16 year olds who drank ormoked in the month prior to the survey among the 43 states thatwitched to a vertical design from 1994 to 2009 (treated). The lines centered in the year each state went vertical (time 0), and tracksonsumption in the years leading up to and after this period (1–2,
–4, 5–6, 7 plus years). As a point of comparison, the dashed linesraph the average percentage of 16 year olds who drank or smokedcross the remaining eight states (control). For these states, we
16 The authors spoke with ABnote North American, which produces over 50% oftates’ licenses.17 Federal suggestions for security improvements are formalized in the REAL IDct of 2005 (Pub.L. 109–13).
A. Bellou, R. Bhatt / Journal of Health
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The DD model is estimated using 16 year olds and is analogousto Eq. (1), but adapted to the two-period (“pre”/“post”) setting. Theresults provide a baseline effect of the license in the restricted data.
ig. 3. Trends in teen smoking and drinking in past month, relative to year verticalicense was adopted.
ollow Ayres and Levitt (1998) and construct average consumption tears before/after time 0 using average consumption in these statesegged to the years in which each treated state adopted a vertical
icense.18
Prior to the switch, rates of smoking and drinking were highern treated states. This is particularly pronounced for smoking inhe 5–6 years before going vertical. However, patterns of drinkingre similar across treatment and control states, suggesting littlevidence of pre-existing trends with respect to this outcome. Formoking, there is a more pronounced decline among treated states,aising concerns that the vertical license may have been adoptedn response to prior trends in smoking. That said, it is impor-ant to note that these graphs only offer descriptive informationbout underage consumption and do not control for important dif-erences across states and years that are included in our formalegression models.
Fig. 3 also previews our main results. In the 1–2 years after theesign change, levels of consumption in treated states droppedelative to controls. In subsequent years, consumption in treatedtates remains relatively flat (smoking) or exhibits an increasedrinking). Moreover, 5–6 years after the license redesign, con-umption rates are relatively similar in treated and control states.verall, the graph suggests that the policy induced an immedi-te, one-time drop in underage use of tobacco and alcohol, butollowing this, there were no additional decreases.
To formally account for pre-existing trends and issues related toolicy endogeneity we extend our DD model in two ways. First, we
nclude state-specific linear and quadratic time trends in Eq. (1),hich control for unobserved factors that trend over time within
state and are correlated with teen outcomes. Second, we re-stimate Eq. (1), but in place of Verticalst, we include a series ofime dummies for the years leading up to a state going vertical1–2, 3–4, 5–6, and 7 plus years before; the omitted category is 1–2ears prior), the year it goes vertical, and the years after it goesertical (1–2, 3–4, 5–6, and 7 plus years after).19
The latter specification serves two purposes. First, the dummieseading up to the switch reflect whether there is any evidencef pre-existing trends, once other covariates are controlled for.
18 As an example, suppose we have three treated states with the following verticalicense adoption dates (A: 1997, B: 2000, C: 2004), and two control states (D, E)hat did not adopt a vertical design by 2009. We construct the average consumptionmong control states in time 0 using consumption levels in states D and E in 1997,000, and 2004. To construct average consumption in the 1 year before (after) time
for control states, we use consumption levels in D and E in 1996, 1999, and 20031998, 2001, and 2005).19 We combine years (1–2, 3–4, etc.) instead of using one-year increments sincehe YRBSS is given biennially. We set our terminal points at 7 plus years to avoidaving small numbers of observations in higher number years.
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Economics 32 (2013) 353– 366 357
econd, this specification allows us to examine the short and longun response to the vertical license. As Fig. 3 indicates, followingts adoption, there is a drop in underage consumption in treatedtates relative to control, but thereafter consumption levels offnd/or increases. There are at least three potential explanationsor this. First, while teens may initially be constrained by the newicense, over time they may substitute toward other methods ofbtaining alcohol and tobacco. Second, it could be that the supplyf fake cards initially lags behind the new licenses, making itarder for teens to access tobacco and alcohol. Third, after theesign switch, retailers may be more likely to ask for identification,ut subsequently revert in behavior. We discuss evidence for thesexplanations in Section 5.
.3. Difference-in-difference-in-differences model
We supplement our analysis with a triple differences (DDD)odel that uses 17–18 year olds who did not receive vertical
icenses as a within state control group. As discussed above, all7–18 year olds observed the year their state went vertical, as wells 18 year olds one year after did not receive a vertical licenses they turned 16 before the new licenses were issued. The DDDodel allows us to control for two types of potentially confound-
ng effects: first we control for unobserved factors that affect theutcomes of all teens living in a particular state (i.e., state marketingampaigns against underage drinking), and second, for unobservedactors that affect teens of the same age, regardless of state ofesidence.20
To implement the DDD model, we must substantially restruc-ure the data, for reasons that will become apparent. First, we dividetates into treated and control groups. Second, for each treated statee define the “pre” period as the first year that we observe YRBSSata for immediately before the state went vertical. The “post”eriod is defined as the year the state adopted the license, or oneear after. “Post” is defined this way because these are the onlyears for which we observe teens with and without the verticalicense in the same state. We drop all observations two years after
state goes vertical, as well as observations for treated states prioro the “pre” period so that we have a single “pre” and “post” yearor each state.21 Third, for the control states, there is no obviousay to define “pre” and “post” since treated states went vertical in
arious years. Since no state went vertical prior to 1994, we definehe “pre” period for controls as any year prior to 1994, and “post”s any year after 1994 (inclusive). Appendix Table A.1 highlightshe state-years we use in the DDD analysis. Note that structuringhe analysis in this way ignores much of the variation in our data,ut is necessary for the DDD design.
We estimate a DD and DDD model with the restructured data.
e estimate:
20 We use 17–18 year olds as the within-state control group rather than youngereens (i.e., 14 year olds) simply because older teens are more likely to hold a license,nd this offers a direct comparison point for how the redesign affects retail pur-hases. That said, in an analysis available upon request, we re-estimate the DDDodel using 14 year olds. We find negative effects of the license, although none of
he estimates are significant due to lower precision (the number of 14 year olds inhe YRBSS is about half that of 17–18 year olds).21 In practice, we also drop 17 year olds one year after a state went vertical, sincehese students would have received the vertical license. Our results suggest thathe effect of the license varies by age, so to be uniform, we only consider 16 yearlds as treated in the DDD model. We also only allow for a single “pre” period to beymmetric. In an analysis available upon request, we re-estimate the DDD modelith all prior years, and find similar results.
358 A. Bellou, R. Bhatt / Journal of Health Economics 32 (2013) 353– 366
Table 1Diff-in-diff estimates of the effect of the vertical license. Sample of 16 year olds.
Verticals is equal to one if a state adopted a vertical licenseetween 1994 and 2009, Postst is equal to one for the “post” periodor each state, and Yist, Xist, Zst are defined as in Eq. (1). The estimatef ˛3 provides the DD result. For the DDD model, we estimate:
All variables are defined as in Eq. (2), and Age16ist is equal to oneor teens who are age 16. The coefficient on the triple interactionı7) provides the DDD estimate. We estimate Eq. (3) for 16–18 yearlds for drinking, and for 16 and 17 year olds for smoking since it isegal for 18 year olds to smoke. We estimate Eqs. (2) and (3) withnd without state fixed effects.
In order to use 17–18 year olds as a within state comparisonroup, there should be no spillover effects onto these teens. Fornstance, if the consumption of alcohol/tobacco by 17–18 year oldss reduced because 16 year olds in the same state have a vertical
tm
icense, then the DDD results will be underestimated. While peerharing almost certainly occurs, it seems likely that the transfer isrom older to younger peers, rather than the reverse. Alternatively,f retailers only look at the orientation of the license following atate’s switch, it may be easier for 17–18 year olds to purchasenderage, since they have horizontal licenses, thus leading theesults to be overestimated. While we cannot rule out spillovers, wean gain insight from the DDD model. The coefficient ı4 captureshe change in consumption for 17–18 year olds before and after 16ear olds in their state received a vertical license, relative to whatappened in control states. If spillovers exist, we should observe aon-zero estimate. In practice, we find no evidence of this.
. Results
22 In an omitted analysis, available upon request, we estimate the impact of the ver-ical license on teen alcohol and tobacco use using a Seemingly Unrelated Regression
odel. The results from this model produce similar estimates.
A. Bellou, R. Bhatt / Journal of Health Economics 32 (2013) 353– 366 359
Table 2Diff-in-diff estimates of the effect of the vertical license. Sample of 17 and 18 year olds.
Individual covariates N Y Y YState covariates N Y Y YState FE Y Y Y YYear FE Y Y Y YState-linear time trend N N Y YQuadratic time trend N N N Y
R are used in all regressions.
fictrnelra((gtpdtTg
doeotc
a
ayt
fW
Table 3Diff-in-diff estimates of the effect of the vertical license. Short and long run effects.Sample of 16 year olds.
DV: Smoke DV: Drink
7–8 years before −0.035 −0.040(s.e.) (0.027) (0.038)
5–6 years before 0.008 −0.035(s.e.) (0.029) (0.037)
3–4 years before −0.009 −0.008(s.e.) (0.023) (0.032)
1–2 years before (omitted) – –Year of vertical license −0.024 −0.016
(s.e.) (0.023) (0.026)1–2 years after −0.041 −0.077
(s.e.) (0.023)* (0.034)**
3–4 years after −0.016 −0.026(s.e.) (0.022) (0.026)
5–6 years after −0.010 −0.040(s.e.) (0.030) (0.034)
7 plus years after 0.058 0.029(s.e.) (0.028)* (0.036)
R2 0.050 0.025N 34,745 34,186
Individual covariates Y YState covariates Y YState FE Y Y
obust standard errors are clustered at the state level and YRBSS sampling weights* Statistically significant at 10% level.
xed effects, Column 2 adds in individual and state time-varyingovariates, and Columns 3 and 4 add in linear and quadratic timerends. In Column 1 we observe a negative impact of the licenseedesign on smoking and drinking, although only the latter is sig-ificant, and no effect on intensity or on chewing tobacco. The pointstimates in Column 2 are more precise and slightly larger in abso-ute magnitude for all outcomes except the intensity measures. Theesults indicate that the vertical license reduced the likelihood that
16 year old smoked in the past month by 3 percentage points10.7% evaluated at the mean), and drank by 3.8 percentage points8%). Again, there are no significant effects at the intensive mar-in. The slightly larger effect on smoking could be due to the facthat more underage teens use stores to purchase cigarettes (30% ofast month smokers in the YRBSS) than alcohol (5% of past monthrinkers).23 Finally, with the inclusion of linear and quadratic timerends, the estimated effects are even larger (in absolute value).24
able 2 presents estimates of Eq. (1) for 17–18 year olds. For bothroups, we find no significant effect of the vertical license.25
The results of the DD model where we include a series of timeummies for the years before and after a state goes vertical (wemit 1–2 years before) are presented in Table 3. We estimate thisquation only for 16 year olds and for Smoke and Drink based onur findings from Tables 1 and 2. Focusing on the years leading up
o the design change, we observe estimates that are not statisti-ally different from zero, vary in sign, and in the years immediately
23 Figures are based on authors’ calculations using YRBSS data. Sources of alcoholre available in the 2007 and 2009 survey years, and for tobacco from 1995 to 2009.24 We also estimated a specification with state-specific cubic time trends as well as
specification that included interactions between region dummies (4 regions) andear dummies (10 survey years). In both cases, results were qualitatively similar tohe effects reported in Table 1.25 In an omitted analysis available upon request, we estimated Eq. (1) for drinkingor a sample of 19–20 year olds in the Behavioral Risk Factor Surveillance System.
e did not find any significant effects of the license.
Year FE Y Y
Robust standard errors are clustered at the state level and YRBSS sampling weightsare used in all regressions. All regressions include the control variables described inthe text.
bs
e
* Statistically significant at 10% level.** Statistically significant at 5% level.
efore the change are particularly small. There is little evidence forystematic, pre-existing trends prior to the switch.26
26 For brevity, for the remainder of the analysis, we omit the results for the depend-nt variables Chewing Tobacco, and Smoke and Drink Frequently. We find no impact
360 A. Bellou, R. Bhatt / Journal of Health Economics 32 (2013) 353– 366
Table 4Diff-in-diff and diff-in-diff-in-diff estimates of the effect of the vertical license. Two period sample.
Individual covariates Y Y Y YState covariates Y Y Y YState FE N Y N Y
Robust standard errors are clustered at the state level and YRBSS sampling weights are used in all regressions.
stfptfa
rdler
4
dpTbnaaieo
om
dospnw1imt
5
5
wmcestT
* Statistically significant at 10% level.** Statistically significant at 5% level.
*** Statistically significant at 1% level.
The estimates for the year of adoption are negative but small andtatistically insignificant. Moving to 1–2 years after a state goes ver-ical, there is a strong, negative and significant (at the 10% (5) levelor smoking (drinking)) effect, indicating a 4 and 7.7 percentageoint reduction in the likelihood of smoking and drinking, respec-ively. In subsequent years the estimates are (with one exceptionor smoking) small, mostly negative and statistically indistinguish-ble from zero.
There are two noteworthy aspects of the results. First, theedesign impacts 16 year olds but not older teens. Second, theynamic results indicate a pronounced effect 1–2 years after the
icense is introduced, and negative, but insignificant effects oth-rwise. In Section 5 we describe potential explanations for theseesults, and discuss the role of measurement error in our analysis.
.2. Difference-in-difference-in-differences
We present the results of the DDD model in Table 4 for theependent variables Smoke and Drink. The first half of the Tableresents the results of the DD model (Eq. (2)) for 16 year olds.he estimates are less precise due to the smaller sample size,ut that said, we continue to find negative and statistically sig-ificant effects (for drinking) of the vertical design: the license isssociated with a reduction in drinking and smoking by 5.8–7.9
nd 5.7–6.7 percentage points, respectively. Given that the orig-nal DD results are upheld in the restructured sample, the DDDstimates will likely provide useful inference on the robustness ofur results.
f the vertical license on these outcomes for older teens (Table 2), in the dynamic DDodel (Table 3) or in the DDD model (Table 4). Results are available upon request.
te
tcldfi
The lower half of the Table 4 presents estimates on the level,ouble and triple interaction terms of the DDD model. Recall, inrder to use 17–18 year olds as within state comparisons therehould be no spillover effect of the license on these older teens. Inractice, the estimates of ı4 are small and insignificant, suggestingo such effects. Turning to the coefficients on the triple interaction,e find a negative effect on smoking and drinking. The probability a
6 year old smokes is reduced by 3.0–4.2 percentage points (albeit,nsignificant) and drinks by 7.3–8.4 percentage points. These esti-
ates are in the range of our findings from Tables 1 and 3. Overallhen, the DDD results uphold the DD findings.
. Discussion
.1. Measurement error
As discussed above, we make a series of assumptions to identifyho has a vertical license, and any misclassification will introduceeasurement error. There are four potential sources of misclassifi-
ation, which we describe below. To gauge the extent to which thestimates are affected by measurement error, we conduct a series ofensitivity analyses. Overall, these analyses indicate that the quan-itative findings are not predominantly driven by misclassification.hat said, to the extent that mismeasurement affects the estimates,he reader should interpret our results as providing a lower boundffect of the vertical license.
The first type of misclassification results from assuming that alleens hold a driver’s license or identification card. Evidence indi-
ates that over the last decade, fewer teens have actually obtainedicenses for driving (Frontier Group, 2012). If an individual does notrive, it seems reasonable that he/she would obtain a state identi-cation card for other purposes (i.e., travel or job applications), and
A. Bellou, R. Bhatt / Journal of Health
Table 5Diff-in-diff estimates of the effect of the vertical license. Assessing measurementerror I: assume 15 year olds receive license first/teens turn 16 before state adoptsthe vertical design. Sample of 15–18 year olds.
Individual covariates Y Y Y YState covariates Y Y Y YState FE Y Y Y YYear FE Y Y Y YLinear time trend N Y N Y
Robust standard errors are clustered at the state level and YRBSS sampling weightsare used in all regressions. All regressions include the control variables described inthe text.
* Statistically significant at 10% level.
tit
iaviti1yacinsaec
omhina
e1TtunaT
etohwgaaoIc
svtr2taufe1ic
vitibWavaallow for more realistic definitions of the policy variable, the resultschange marginally.
28 The same falsification test was conducted using 14 year olds (available uponrequest), where we found no effects.
29 Consider the following example. Suppose a state switched to the vertical licensein June 2005 and that we observe 16–18 year olds in 2005–2007. In 2005, we willmisclassify all 16 year olds who turned 16 prior to June 2005 as having a vertical
** Statistically significant at 5% level.*** Statistically significant at 1% level.
hese cards underwent the same vertical design change. That said,f a teen does not hold identification of any kind, this will contributeo our results being attenuated.27
Second, teens may receive their license as early as age 15. If thiss the case, our main analysis not only ignores 15 year olds, butlso mistakenly classifies 16–18 year olds as having received theertical license one year earlier than they actually did. To exam-ne this, we re-estimate Eq. (1) assuming that teens first receiveheir license at 15. In our earlier example of a state going verticaln 2005, this implies the following teens have a vertical license:5 year olds in 2005 and subsequent years, and 16, 17, and 18ear olds in 2006, 2007, 2008 and forward, respectively. The resultsre provided in Table 5. We find no effect for 15 year olds, whichould reflect that in practice very few of them have a license, orf they do, they require supervision to drive which limits opportu-ities for underage purchases. The estimates for 15 year olds alsoerve as a “falsification test”. If teens actually receive their license
t 16, then assigning licenses to 15 year olds should result in zerostimated effects so long as there are no unobserved state spe-ific factors driving the results. The estimates in Table 5 provide no
27 In an omitted analysis (available upon request), we estimate Eq. (1) for 16 yearlds living in rural, suburban and urban areas. Teens in rural and suburban areasay be more likely to drive relative to their counterparts in urban areas who likely
ave greater access to public transportation. Urbanicity measures are only availablen the 1997, 1999, 2001, and 2003 survey years. The results indicate a stronger,egative effect of the license on underage consumption for teens in suburban/ruralreas, which is consistent with having less measurement error for this group.
l2tatJ1oIae
ig
Economics 32 (2013) 353– 366 361
vidence that unobservables drive our main findings.28 For 17 and8 year olds, we continue to find small and insignificant effects.his suggests that even if the results in Table 2 are attenuated dueo incorrectly assuming that teens obtain a license at 16, the atten-ation is not so severe that it causes us to falsely conclude there iso effect for older teens. For 16 year olds, the effects of the licensere significant and even more negative than those presented inable 1.
The third, and perhaps most pervasive source of measurementrror stems from assuming all 16 year olds observed in the yearheir state went vertical had a vertical license, as did 17 (18) yearlds one (two) years later. In practice, some of these teens likelyeld horizontal licenses because they turned 16 before their stateent vertical. This will only affect our classification of the following
roups: (i) 16 year olds in the year a state went vertical and one yearfter, (ii) 17 year olds one year after, and (iii) 18 year olds two yearsfter.29 Such misclassification could explain why, in Table 3, we findnly a small negative effect in year 0 (compared to 1–2 years after).f many teens in this year are misclassified, this will attenuate theoefficient estimates.
We consider the sensitivity of the results to this type of mea-urement error by considering three alternative definitions of theariable Vertical. First, we assume that all teens observed in the yearheir state went vertical turned their current age before the licenseedesign. Following our earlier example of a state going vertical in005, this implies 16 year olds observed in 2006 and forward werereated, as well as 17 and 18 year olds observed in 2007 and 2008nd forward, respectively. This classification is identical to the onesed to produce the results in Table 5. We find no significant effector 17–18 year olds, but do find effects for 16 year olds which areven larger than those in Table 1. This suggests the proportion of6 year olds who are misclassified as having the vertical license
n the year a state goes vertical is non-negligible, thus biasing theoefficient estimate in year 0 toward zero.
As a second definition, rather than construct Vertical as a binaryariable, we assign a “fractional value” between 0 and 1 for teensn the year their state went vertical. The fraction represents hypo-hetical lengths of a year during which a vertical license might bessued (i.e., if a state went vertical in April 2005, the licenses woulde issued in 9 out of 12 months (3/4); July (1/2); October (1/4)).30
e continue to assign a value of 0 for all years prior to the switch,nd 1 for all years after. We present the results for a set of “fractionalalues” in the upper half of Table 6 for 16 year olds. The estimatesre similar to those in Tables 1 and 5, suggesting that even if we
icense. We will also misclassify the 16 year olds in 2006 that turned 16 prior to June005. It is impossible for any of the 16 year olds in 2007 to have turned 16 prioro 2005, and thus we will not have any misclassification for 16 year olds in 2007nd later. For 17 and 18 year olds, we will misclassify the 17 year olds in 2006 thaturned 16 prior to June 2005, and the 18 year olds in 2007 that turned 16 prior toune 2005. Beyond these years, we will not have any misclassification for 17 and8 year olds, respectively. Such misclassification can explain, for instance, why webserve larger effects of the license for 16 year olds in Table 5 compared to Table 1.n Table 5, we now classify 16 year olds observed in the year their state went verticals not having received the vertical license, thus potentially reducing measurementrror.30 For simplicity, we assume that all states that adopted a vertical license did son the same month. Dee et al. (2005) use fractional values to examine the effect ofraduated driver’s license laws on teen traffic fatalities.
362 A. Bellou, R. Bhatt / Journal of Health Economics 32 (2013) 353– 366
Table 6Diff-in-diff estimates of the effect of the vertical license. Assessing measurementerror II: assign fractional values, omit observations, assume 17–18 year olds receivea vertical license at the same time as 16 year olds.
Set vertical = fractional value in year state adopts vertical license. 16 year olds
Individual and state covariates Y YState and year FE Y Y
Robust standard errors are clustered at the state level and YRBSS sampling weightsare used in all regressions. All regressions include the control variables described inthe text.
** Statistically significant at 5% level.*** Statistically significant at 1% level.
o(TcfpTp
l
cag
-0.2
-0.1
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7store
give $ tosomeone tobuy for me(omit)bum
vend /steal/other
3+ 1-2 0 1- 2 3-4 5+
FS
au
5
ctstieaislt
tmtt(swddin Eq. (1) (we omit 3 plus years before).32 We graph the coefficientson the time dummies in Fig. 4 (base category is “gave someonemoney”). In the years leading up to the switch, store purchases and
31 In an analysis (available upon request) the authors calculated bounds for theeffect of the vertical license on underage consumption using the methods outlinedby Aigner (1973) and Bollinger (1996, 2001). We calculate these bounds under dif-ferent assumptions about the extent of measurement error in the binary variable.Overall, the results suggest that even in the presence of measurement error ourfindings in Tables 1–6 are informative.
32 An additional category, “A person above 18 gave them to me” was added inthe 2001–2009 surveys. To maintain uniformity in response categories through-out the 1995–2009 sample, we omit this response from the analysis. We groupsteal/vending/other into a single category to increase cell size. We include a seriesof time dummies for the years prior to a state going vertical (1–2, 3 plus) the yeara state goes vertical, and the years after (1–2, 3–4, 5 plus). We group all years priorto 3 years before adoption to increase cell size. That is, because information aboutwhere teens obtain cigarettes only began to be collected in 1995, there is little infor-mation for the earliest adopting states (i.e., 1994 or 1996) about where teens accesscigarettes prior to adoption. We estimate the model for 16–17 year olds (N = 14,129).
As a final check, we re-estimate our DD model without thebservations that are susceptible to this type of misclassificationgroups (i)–(iii)). The results are shown in the middle of Table 6.he estimates for 16 year olds are smaller than before, but stillonsistent with the results in Table 1. We continue to find no effector older teens. This check is less than ideal since it results in lowerrecision. Nonetheless, this finding, combined with the results inable 5 suggests that our main results are robust to even the mostroblematic types of misclassification.
The final type of mismeasurement arises if teens with horizontalicenses obtain vertical ones.
We cannot gauge the extent to which this occurs; however, wean examine how the results change if all 17–18 year olds obtained
vertical license when their state went vertical. The results areiven in the lower half of Table 6. The effects are opposite-signed
Ni
ig. 4. Effect of vertical license on sources of tobacco. Diff-in-diff multinomial logit.ample of 16 and 17 year olds.
nd insignificant, again suggesting the null effect for older teens isnlikely to be driven by measurement error.31
.2. Mechanisms
Our results indicate that the vertical license reduced underageonsumption for 16 year olds, but not for older teens. Moreover,he effects are concentrated in the first 1–2 years after the licensewitch. Subsequently, there is no additional decline in consump-ion. There are several potential explanations: (i) while teens maynitially be impacted by the license, over time they gain experi-nce and find other ways to consume these products, (ii) there isn initial drop in the availability of false identification cards follow-ng the policy change which restricts consumption, but thereafterupply catches up with demand, and (iii) at first retailers are moreikely to check for identification but subsequently revert to sellingo minors for profit motivations.
To gauge evidence for these explanations we turn to data fromhe YRBSS on sources of tobacco. Teens that smoked in the past
onth were asked where they obtained cigarettes, and we grouphese responses into four categories: (i) store (30% of teens usedhis method), (ii) gave someone money to buy them for me (28%),iii) bummed them (29%), and (iv) obtained from vending machine,tole, and other (13%). We estimate a multinomial logit DD modelhere the dependent variable is the cigarette source, and indepen-ent variables are a series of time dummies for the years before,uring and after a state went vertical, along with all the covariates
one of the coefficients is statistically significant because the standard errors aremprecisely estimated. Regression results are available upon request.
A. Bellou, R. Bhatt / Journal of Health Economics 32 (2013) 353– 366 363
Table 7Diff-in-diff estimates of the effect of the vertical license on showing identification and retailer violations.
16 year olds 17 year olds Mean
DV: asked to show IDVertical 0.093 −0.078 16 year olds 0.353(s.e.) (0.055)* (0.046)* [0.478]R2 0.1071 0.0769 17 year olds 0.365N 3125 4064 [0.482]
Individual and state covariates Y YState and year FE Y YLinear time trend N Y
Robust standard errors are clustered at the state level and YRBSS sampling weights are used in all regressions. All regressions include the control variables described in thet
viscoctto
TdtseyiatkoA
c(athoiiart
iffilsaat
iblicAhatu
tSwartosgd
34 We would like to thank an anonymous referee for suggesting this possibility.According to the U.S. Department of Justice (2011), there are three ways teens obtainillegal identification: borrow an ID from an older sibling or an unknown person (thisaccounts for 95% of cases), obtain a fraudulent ID (typically online) or alter an exist-ing ID (the photo or the birth date). The vertical redesign along with the additionalsecurity features presumably made it harder to alter legitimate IDs, and/or more
ext.* Statistically significant at 10% level.
ending/steal/other are relatively flat, and there is a slight increasen bumming. After the switch, there is a decrease in purchases fromtores and bumming, indicating that it may have become diffi-ult for teens to purchase cigarettes directly. In contrast, the usef vending/stealing/other slightly increases. Over time, store pur-hases level off and then decline, and there is greater movementoward the other two sources. Overall, these results suggest thathe license reduced store purchases, but teens were able to usether sources to obtain tobacco.
An additional piece of evidence is provided in the upper half ofable 7. Here we present the results of Eq. (1), where we replace theependent variable with an indicator for whether a teen was askedo show identification when he/she purchased cigarettes from atore (conditional on smoking and purchasing from a store). Westimate the model separately for 16 and 17 year olds. Among 16ear olds, the probability of being asked to show identificationncreases by 9 percentage points, whereas it drops by 8 percent-ge points for 17 year olds. These results suggest that followinghe design change, inexperienced 16 year olds are less likely tonow which retailers do not ask for identification, whereas 17 yearlds, who have held the license for a year, are more knowledgeable.gain, this is consistent with a story of learning.33
A second explanation of our results is that following the designhange, it was harder for teens to obtain fake identification cardswith horizontal orientation and false birthdates). As discussedbove, at the same time that states switched to the vertical design,hey also adopted other security measures that made licensesarder to tamper with or replicate. It could be that the productionf false identification cards lagged behind the new vertical licensesn the 0–2 years following the redesign, but afterwards, the supplyncreased and underage teens were able to obtain fake cards
nd make underage purchases. Unfortunately, little data existsegarding the use of fake cards, and we are not able to empiricallyest this explanation. We do know, however, that the use of false
33 In an effort to understand the null effects on the intensity measures (Table 1),n an omitted analysis (available upon request) we estimated this model separatelyor 16 year old teens that reported smoking frequently and teens that did not. Wend that upon the design change, frequent smokers were 7.9 percentage points less
ikely to be asked for an id when purchasing tobacco from a store whereas occasionalmokers were 24.8 percentage points more likely. These findings are also in line with
learning explanation, whereby habitual teen smokers respond more “strategically”nd adapt faster to the restrictions raised by the license redesign, thus mitigatinghe effects of the license redesign on underage tobacco consumption.
deaTa
sptmoGduiue
dentification is illegal in all fifty states and D.C., and is punishabley jail time and/or monetary fines which may reduce teens’
ikelihood of using it. That said, such punishment will only resultf teens are caught and turned in, and rates of ownership of fakeards have been found to be non-trivial. In the 2001 Collegelcohol Study, close to 6% of underage college students reportedaving a fake id. Overall, the potential interaction of fake cardsnd the new vertical design suggests that our results may reflecteens’ restricted access to false identification cards, thus loweringnderage consumption initially.34
Finally, to study retailer responses to the vertical design, we turno data on tobacco retailer compliance checks conducted under theynar Amendment. We estimate a DD model (similar to Eq. (1)),here the dependent variable is a binary indicator equal to one if
state’s target rate exceeds their violation rate in a given year. Theesults are presented in the lower half of Table 7. We find a posi-ive relationship between the license redesign and the likelihoodf meeting the target, although the estimates are small and nottatistically insignificant. Overall, then, there is little evidence sug-esting that retailer behavior changed in response to the verticalesign.35
ifficult for manufacturers to produce high quality fake copies and therefore morexpensive for underage teens to buy them. Following media reports, the price of
fake ID can be as high as $300 and falls as they are ordered in larger quantities.he average price is approximately $100 (Halsey, 2011). It is less clear whether thebility to access borrowed IDs was reduced as a result of the license redesign.35 All covariates listed in Eq. (1) are included in the retailer violation rate regres-ion, except for the individual covariates. We also control for the 15–20 year-oldopulation in each year and state. There are two issues regarding the Synar datahat may limit inference from this analysis. First, a 2001 report by the U.S. Govern-
ent Accountability Office (GAO) indicates that some states did not conduct checksn a random sample of tobacco retailers, which can bias the results. Second, theAO report indicates that a number of states used teens younger than 16 to con-uct checks, thereby increasing the likelihood that retailers would identify them asnderage. We also estimate the model with time dummies for the years before, dur-
ng, and after a state implements a vertical license (omitted for brevity, but availablepon request; 1–2 years prior is omitted), and we find positive (but insignificant)ffects on the probability of meeting the target rate in the years after going vertical.
364 A. Bellou, R. Bhatt / Journal of Health Economics 32 (2013) 353– 366
Table 8Diff-in-diff estimates of the effect of the vertical license on drug use and drunk driving fatalities. Sample of 16 year olds.
Individual and state covariates Y Y Y YState and year FE Y Y Y YLinear time trend N Y N Y
Robust standard errors are clustered at the state level. See text for information on samples used and variable definitions.
5
aPjCctGsw
fesissu
wtuooas
Fbomirlbsncnt
cn
6
ccgdt
tsatdt
nros2012). Applying this ratio to the 16 year olds that drink in theYRBSS, our finding that there is a reduction in drinking of 3.8–5 per-centage points suggests a cost savings of 1.4–1.9 million per year.
36 Data on the number of licensed drivers from 1994 to 2009 are available from theFederal Highway Administration. Following Ruhm (1996), regressions are weightedto account for heteroskedasticity. In an omitted analysis (available upon request),we examine the impact of the vertical license on crashes involving 17–18 year olds.We consistently find effect sizes that are small, not statistically significant and varyin sign.
37 For instance, in Michigan, supporting organizations include Beer & WineWholesalers Association, Distributors and Vendors Association, Food and BeverageAssociation, Grocers Association, Police, Mothers/Students Against Drunk Driving.In conversations between the authors and one of the largest manufacturers of states’licenses, it was determined that the consumers’ costs for a vertical license are not
* Statistically significant at 10% level.
.3. Drug use and drunk driving fatalities
In this section we examine whether the vertical license hasn (indirect) impact on drug use and drunk driving fatalities.rior literature suggests there is a correlation between mari-uana and alcohol use (DiNardo and Lemieux, 2001; Nationalrime Prevention Council, 2011). In addition, motor vehiclerashes are the number one killer of teens in the U.S. andhey often involve alcohol (Center for Disease Control, 2010a,b).iven the negative impact of the vertical license on alcohol con-umption, there may be indirect effects on these outcomes asell.
To examine the impact on drug use, we estimate a DD modelollowing Eq. (1) for 16 year olds, where we replace the depend-nt variable with an indicator for whether or not the teen reportedmoking marijuana in the past month. The results are providedn the upper half of Table 8 (Columns 1 and 2). We find noignificant effect on marijuana use, even when we include state-pecific time trends, suggesting there are no residual effects on drugse.
To evaluate the impact of the license on teen traffic fatalities,e turn to two sources. First, in the YRBSS teens are asked whether
hey drove a car after drinking alcohol in the past month. In thepper half of Table 8 (Columns 3 and 4) we provide the resultsf Eq. (1) for 16 year olds using self-reported drunk driving as theutcome. The results suggest that teens are less likely to drive drunkfter the design change but the effect is small and only weaklyignificant.
Next, we turn to state-level data on traffic fatalities from theARS. For each year from 1994 to 2009, we observe the num-er of drivers involved in a fatal car crash by age and statef license. Following Dills (2010) and Ruhm (1996), we esti-ate a DD model as in Eq. (1), where the dependent variable
s ln((involvement rateit)/(1 − involvement rateit)). The “involvementate” is defined as the number of 16 year old drivers in a givenicense state i and year t that are involved in fatal car crashes dividedy the state’s population of all 16 year old licensed drivers. Wetudy accidents that happened at any time during the day and also
ighttime accidents (Dee and Evans, 2001; Grant, 2010). In bothases we find no strong evidence that the policy switch had a sig-ificant effect on the number of 16 year-old drivers involved inraffic fatalities. However, we do find a stronger effect on nighttime
duwlt
rashes; the estimates are larger in magnitude and statistically sig-ificant at 10% level when state-specific time trends are included.36
. Conclusion
To the best of our knowledge, this is the first study to empiri-ally examine the impact of the vertical license design on underageonsumption. The dearth of information on the topic is surprisingiven the popularity of the policy and public support for it. The newesign was supported by multiple stake holders from all sides ofhe debate, and is arguably low-cost.37
We find that the vertical redesign reduced underage consump-ion for 16 year olds in the 1–2 years following its adoption butubsequently there was no further decrease. We find no effectmong older teens. Moreover, the results do not suggest substitu-ion to other drugs, but do suggest a weak negative effect on drunkriving. We rationalize these results in the context of teen learning,he availability of false identification cards, and retailer behavior.
Taken at face value, our findings indicate that there is an eco-omically meaningful effect of the vertical license. For instance,ecent research has found that 1 out of 18 teens between the agesf 15 and 20 are hospitalized each year for alcohol-related rea-ons, and that the average cost of treatment is $19,210 (Kim et al.,
ifferent from traditional horizontal licenses. Moreover, since individuals who werender 21 but received their license before their state switched to the new designere not required to obtain a new license, this limits “bureaucracy costs” of the
icense. As a result, however, it takes close to 5 years for every individual under 21o have a vertical license once a state makes the design switch.
A. Bellou, R. Bhatt / Journal of Health Economics 32 (2013) 353– 366 365
Table A.1Year of vertical license and YRBSS survey years.
State Year of vert. YRBSS survey years
1991 1993 1995 1997 1999 2001 2003 2005 2007 2009
Alaska 2004Alabama 2005 X X X X X X X XArkansas 2006 X X X X X XArizona 2001 X X X X X X X XCalifornia 2010 X X X X X X X X X XColorado 1994 X X X X X XConnecticut 2002 X XDC 2004 XDelaware 1996 X XFlorida 2004 X X X X X X X X X XGeorgia 2009 X X X X X X X X X XHawaii 2005 X XIowa 2001 X X X XIdaho 2002 X XIllinois 2005 X X X X X X X X XIndiana 2007 X X X X XKansas 2004 X X X X XKentucky 2001 X XLouisiana 2001 X X X X X XMassachusetts 2004 X X X X X X XMaryland 2003 X X X XMaine 2011 X X X X X XMichigan 2003 X X X X X X X X X XMinnesota No X X XMissouri No X X X X X X X X XMississippi 2001 X X X X X X XMontana 2008 XN. Carolina 2008 X X X X X X XN. Dakota 2006Nebraska 2003 XN. Hampshire 2008 XN. Jersey 2004 X X X X X X X XN. Mexico 2000 X X X X X X XNevada 2002 X XNew York No X X X X X X X X X XOhio 2002 X X X X X X X XOklahoma 2003 X X X XOregon No X X X XPennsylvania 2001 X X X X X X X X XRhode Island 2002 XS. Carolina 2011 X X X X X XS. Dakota 2009 X XTennessee No X X X X X X XTexas 2001 X X X X X X X X X XUtah 2006 X X XVirginia 1999 X X X X X X XVermont 2003 X XWashington 2001 X X X X X X XWisconsin 2005 X X X X X X XW. Virginia 1999 X X X X X
U DDD a
MsU3trdt
h3piy
dlet
Wyoming 2005
nderlined observations refer to the state-year combinations that are used for the
oreover, research indicates that 68% of adult smokers began tomoke before the age of 18 (American Lung Association, 2010).sing our estimates that the vertical license reduces smoking by–4.3 percentage points (among 16 year olds) this suggests thathere would be 11–15% fewer adult smokers. Holding the death
ate associated with smoking-related diseases constant at 0.855eaths per 100 adult smokers (this excludes second-hand smoke),his translates to a commensurate drop in mortality (CDC, 2008).38
38 In the YRBSS there are 16726.3 drinkers of whom 929.2 are estimated to beospitalized based on the 1 in 18 ratio. The vertical license reduces drinking by.8–5 percentage points, which would drop down hospitalizations to 831.2–854.7ersons. Multiplying the reduction in hospitalization by the average cost of $19,210
mplies savings of 1.4–1.9 million. For smoking, in the YRBSS there are 10027.4 16-ear old smokers. If 68% of adult smokers started smoking before the age of 18, this
aeass
iloa
nalysis (see Section 3.3).
Our analysis has some limitations. First, as in most otherifference-in-differences studies examining the effect of a state-
evel policy, the potential that the results are biased due to policyndogeneity exists. That said we make a concerted effort to con-rol for other state policies which could affect teen outcomes,s well as state-specific time trends, and still find significantffects of the new design. Moreover, the results are robust to
triple difference specification designed to net out unobservedtate-specific factors. Second, our inability to observe student pos-ession of licenses introduces measurement error. However, this
mplies a total of 14,746.2 adult smokers (10027.4 divided by 0.68). The verticalicense reduces smoking by 3–4.3 percentage points, implying a drop in the numberf adult smokers to 12,481.6–13,166.2. This is an 11–15% drop in the population ofdult smokers.
3 ealth
mtir
A
R
A
A
A
A
A
A
B
B
B
B
C
C
C
C
C
C
C
C
C
C
D
D
D
D
D
D
E
F
G
G
H
K
I
L
L
M
M
N
N
O
R
R
R
S
U
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66 A. Bellou, R. Bhatt / Journal of H
isclassification actually causes us to estimate lower bounds forhe effect of the license, which still provides relevant and usefulnformation for public officials tasked with developing policies foreducing underage consumption.
ppendix A.
Table A.1.
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