ALCOHOL PREVALENCE, ALCOHOL POLICIES, AND CHILD FATALINJURY RATES FROM MOTOR VEHICLE CRASHES

BISAKHA SEN and CHRISTINE M. CAMPBELL∗

In this study, we consider the effects of state alcohol policies on motor vehiclefatalities for children. While numerous studies have considered the effects of suchpolicies on motor vehicle fatalities for the overall population, for teens, and for theelderly, their effects on fatalities among children in particular have not previouslybeen studied. We use state-level cross-sectional time series data for 1982–2002.The dependent variable of interest is fatalities among child motor vehicle occupants(CMVO). Separate models are estimated for 0- to 4-yr-olds, 5- to 9-yr-olds, and 10- to15-yr-olds, as well as for fatalities occurring during the day versus the night. We findthat number of fatalities among CMVO is strongly correlated to alcohol use measuredat the state level and that administrative license revocation policies and higher beer taxrates appear to consistently reduce such fatalities. For two of the three age groups, beertax rates appear to reduce fatalities during the night rather than the day. However,zero tolerance and blood alcohol concentration limit laws do not seem to have anystatistically significant effects on fatalities. (JEL I18, J13)

I. INTRODUCTION

Motor vehicle crashes are the leading con-tributor to fatal injuries from accidental/uninten-tional causes for all age groups. Among children,motor vehicle crashes are the leading cause ofdeath in the 5–14 age group, and the secondleading cause of death (after “all other accidentsand adverse effects”) for the 0–4 age group.1

Therefore, it is valuable from a policy perspec-tive to determine what laws are useful in reduc-ing such fatal injuries among children.

It is well established that an important riskfactor for a motor vehicle accident is alco-hol use by drivers. Over the past two decades

*This project was supported by funding from the Sub-stance Abuse Policy Research Program, Robert Wood John-son Foundation. We are grateful for comments from MichaelMorrisey, Frank Sloan, Don Kenkel, participants of the 2005SAPRP annual conference, participants of the 2006 WEAIconference, and two anonymous referees.Sen: Associate Professor, Department of Healthcare Organi-

zation & Policy, University of Alabama at Birmingham,Ryals School of Public Health 330, 1665 UniversityBoulevard, Birmingham, AL 35294. Phone 205-975-8960, Fax 205-934-3347, E-mail bsen@uab.edu

Campbell: Medical Student and Research Assistant, Uni-versity of Alabama School of Medicine, Medical Stu-dent Services, Volker Hall 100, 1530 3rd AvenueSouth, Birmingham, AL 35294. Phone 205-586-5315,Fax 205-934-8866, E-mail ccpinocuasom@uab.edu

1. CDC, Disaster Center. Accessed December 27, 2006.http://www.disastercenter.com/cdc/.

states have introduced a number of legal inter-ventions to reduce the incidence of alcohol-impaired driving, or “driving under the influ-ence” (DUI), such as illegal per se blood alcoholconcentration (BAC) limits and administrativelicense revocation (ALR). States have also intro-duced legal interventions specifically targeted atreducing alcohol use among youth, such as theminimum legal drinking age (MLDA) of 21 and“zero tolerance” laws. Such interventions appearto be associated with temporal declines in thenumber of alcohol-related motor vehicle crashesas well as a decrease in associated mortality. TheNational Highway Traffic Safety Administra-tion (NHTSA) reports that during 1982–2002,the proportion of motor vehicle fatalities thatwere alcohol-related (where at least one driverhad a BAC ≥0.01) decreased from 60% to 41%

ABBREVIATIONSALR: Administrative License RevocationBAC: Blood Alcohol ConcentrationCDC: Centers for Disease Control and PreventionCMVO: Child Motor Vehicle OccupantsDUI: Driving under the InfluenceFARS: Fatality Analysis Reporting SystemMLDA: Minimum Legal Drinking AgeNHTSA: National Highway Traffic Safety

Administration

392Contemporary Economic Policy (ISSN 1465-7287) doi:10.1111/j.1465-7287.2009.00142.xVol. 28, No. 3, July 2010, 392–405 © 2009 Western Economic Association InternationalOnline Early publication November 25, 2009

SEN & PINO: ALCOHOL POLICIES AND MOTOR VEHICLE FATALITIES FOR CHILDREN 393

FIGURE 1Percent of Motor Vehicle Fatalities Related to Alcohol by BAC, 1982–2002

0%

10%

20%

30%

40%

50%

60%

70%

'82 '84 '86 '88 '90 '92 '94 '96 '98 '00 '02'04

YEAR

PE

RC

EN

Tnot alcohol related(BAC=.00)

all alcohol related(BAC>.01)

alcohol related(BAC>.08)

Notes: Data for this chart are from NHTSA, U.S. Department of Transportation (2006)—Traffic Safety Facts 2004, chapter1, table 13: Persons killed, by highest blood alcohol concentration (BAC), in crashes, 1982–2002.

and those involving a BAC of 0.08 or moredecreased from 53% to 35% (Figure 1).2 Duringthe same time period, the overall fatality rate ofalcohol-related crashes declined from 11.3 to 6.1per 100,000 population.3

Extant empirical literature generally supportsthe effectiveness of DUI laws in reducing motorvehicle fatalities among the overall populationand among teens, but no study that we areaware of has specifically examined their effectson child fatality. Motor vehicle fatality ratesamong children are substantially lower thanthose among adolescents and adults. Figure 2shows that fatality rates among children aged0–15 yr have been less than 7 per 100,000 pop-ulation since 1982.4 This contrasts sharply withrates for adolescents of driving age (16–20),for whom fatality rates have ranged from 38.6to 29.2. For the population as a whole (inclu-sive of children and adolescents of drivingage), the rates have ranged from 15.4 to 13.0.5

Following a national trend in the reduction of

2. NHTSA, U.S. Department of Transportation(2006)—Traffic Safety Facts 2004, chapter 1, table 13:Persons killed, by highest blood alcohol concentration(BAC), in crashes, 1982–2002.

3. Calculated using NHTSA, U.S. Department of Trans-portation (2006)—Traffic Safety Facts 2004, chapter 1, table13: Persons killed, by highest blood alcohol concentration(BAC), in crashes, 1982–2002; and chapter 1, table 2: Per-sons killed or injured and fatality and injury rates per popula-tion, licensed drivers, registered vehicles, and vehicle milestraveled, 1966–2002.

4. NHTSA, U.S. Department of Transportation(2006)—Traffic Safety Facts 2004, chapter 1, table 6:Motor vehicle occupant and motorcycle rider fatality andinjury rates per population by age group.

5. Note that the fatality rates mentioned here are calcu-lated in the simplest way—per 100,000 of the populationin the age group. Children, particularly those below school

the rate of fatalities of all ages during thistime, fatality rates for CMVO have also gen-erally decreased—for children younger than 5yr old, it has dropped from 4.50 to 2.52 per100,000 population and for children aged 5–9yr, it has dropped from 2.71 to 2.26 per 100,000population.6 Nevertheless, motor vehicle fatal-ities among children continue to be a seriousconcern. Motor vehicle crashes are the leadingcause of death and disability among children,7

accounting for almost half (44%) of pediatricdeaths (aged 0–14) due to injury. A 2004 Cen-ters for Disease Control and Prevention (CDC)report in the Morbidity and Mortality WeeklyReport stated that 2,355 children died in alcohol-related motor vehicle crashes between 1997and 2002, of whom 1,588 (68%) were ridingwith drinking drivers. Minors who are drink-ing drivers contribute substantially to this prob-lem—Margolis, Foss, and Tolbert (2000) foundthat drivers younger than 21 yr who had beendrinking accounted for 30% of alcohol-relatedpassenger deaths among children between 1991and 1996.

Outrage over continued DUI-related childfatalities has led to some scholars calling for

age, are likely to spend less time in cars than adults or ado-lescents and are less likely to be in cars at nighttime. If wewere able to calculate fatality rates for vehicle miles trav-eled by each age group then the rates for children versusadolescents and adults might have looked quite different.Unfortunately, calculating such fatality rates is beyond thescope of this study.

6. NHTSA, U.S. Department of Transportation(2006)—Traffic Safety Facts 2004, chapter 1, table 6:Motor vehicle occupant and motorcycle rider fatality andinjury rates per population by age group.

7. CDC, http://www.cdc.gov/ncipc/about/about.htm.

394 CONTEMPORARY ECONOMIC POLICY

FIGURE 2Motor Vehicle Fatality Rates per 100,000 Population

0

5

10

15

20

25

30

35

40

'82 '84 '86 '88 '90 '92 '94 '96 '98 '00 '02

YEAR

RA

TE

..

age 0-4age 5-9age 10-15age 16-20all ages

Notes: Data for this chart are from NHTSA, U.S. Department of Transportation (2006)—Traffic Safety Facts 2004, chapter1, table 6: Motor vehicle occupant and motorcycle rider fatality and injury rates per population by age group.

more stringent alcohol policies, including lowerlegal BAC limits for drivers with a child pas-senger (Quinlan et al., 2000), higher beer prices(Margolis, Foss, and Tolbert, 2000), and even azero tolerance policy for alcohol-impaired driv-ing akin to the one for alcohol-impaired flying(Li, 2000). However, since no study has specif-ically considered whether and to what extentextant alcohol policies have reduced such fatal-ities among children, it seems useful to firstexamine that before recommending even morestringent policies.

In this study, we explore the relationshipbetween state alcohol policies and child fatalinjuries in motor vehicle crashes using state-level cross-sectional time series data over1982–2002. We separately consider fatal injuryrates for 0- to 4-yr-olds, 5- to 9-yr-olds, and10- to 15-yr-olds and estimate count data mod-els with state and year fixed effects. We findsome evidence that stricter DUI-related policiesreduce fatal injuries among child motor vehi-cle occupants (hereafter CMVO), but the resultsare not always consistent across the three agegroups. Higher beer tax rates appear to havemore consistently negative and more statisticallyprecise effects on child fatal injuries than mostof the individual DUI policies.

II. BACKGROUND

Children are frequently the victims of alco-hol-related crashes. About a quarter of all childpassenger fatalities involve a drinking driver(CDC, 1997). Eight hundred and ninety chil-dren younger than 15 yr died in crashes that

involved drinking drivers during 1985–2002(CDC, 2004; Quinlan et al., 2000). Quinlan et al.(2000) also note that the percentage of child pas-senger fatalities that involved a drinking driverdecreased from 31% to 23% between 1985 and1996 and that during the same period, the fatal-ity rate for CMVO dropped 26%. This reflectsthe previously mentioned trend for less impaireddriving and a decrease in associated mortality.Since numerous state alcohol policies pertain-ing to DUI were introduced over this period,it is possible that such policies played a rolein reducing these fatalities. However, to ourknowledge, this specific issue has not previouslybeen empirically studied, and this study aimsto fill that gap. This topic is also of particu-lar interest because children in the age groupswe consider are not drivers themselves and arehenceforth truly “innocent victims.” Thus, ifDUI policies and other alcohol policies reducefatality rates among children from motor vehi-cle crashes then they do so only via affectingthe drinking behavior of adults and adolescentsof driving age, and therefore they reduce oneof the most pernicious negative externalities ofalcohol use.

We follow with a brief review of the mainDUI-related state laws and other alcohol policiesthat are considered in this study.

• “Per se” BAC laws make it illegal fora driver to have a BAC above an establishedlimit regardless of an appearance of intoxication.A basis for setting BAC limits comes in partfrom the findings of Borkenstein et al. (1964)

SEN & PINO: ALCOHOL POLICIES AND MOTOR VEHICLE FATALITIES FOR CHILDREN 395

that the likelihood of being in a crash is posi-tively correlated with driver BAC. When conve-nient and reliable tests for alcohol in the bodybecame available, it became possible for statesto set specific BAC limits. The first standardswere passed in the 1960s and were generallyset at 0.15 BAC (Voas, Tippetts, and Tay-lor, 2000; Zador et al., 1989). Over time, theaccepted limit dropped to 0.10 and more statesadopted limits so that by 1984, three quartersof U.S. states had per se laws. Zador et al.(1989) found evidence that per se laws wereassociated with a decline in fatal crashes forsome drivers. Further, researchers discoveredthat impairment in driving skills due to alco-hol begins with even small BAC levels, sug-gesting that the standard 0.10 BAC limit mightbe too high (Moskowitz and Burns, 1990). In1983, Oregon and Utah were the first statesto impose BAC limits of 0.08. By the late1990s, most states had BAC limits in placewith 18 states having 0.08 as the legal upperlimit. In 2000, the federal government passeda bill requiring states to enact 0.08 BAC perse laws by 2004 or begin losing federal high-way construction funds. All 50 states and theDistrict of Columbia have now adopted 0.08BAC per se laws. Though Foss, Stewart, andReinfurt (2001) reported no reduction in fatali-ties after North Carolina lowered its legal limitto 0.08 BAC, numerous other studies did findthat lowering the BAC reduces alcohol-relatedfatalities (Apsler et al., 1999; Hingson, Heeren,and Winter, 2000). Several studies have sincefound an association between 0.10 and 0.08BAC per se laws and a reduction in motorvehicle fatalities (such as Dee, 2001; Eisenberg,2003; Villaveces et al., 2003; Voas, Tippetts, andFell, 2000). On the other hand, Morrisey andGrabowski (2005) found BAC limits to havesmall and often insignificant effects on trafficfatalities among just the elderly, suggesting thatthe laws may not equally impact traffic fatalityrates among all age groups. Notably, there issome evidence suggesting that drivers commit-ting DUI with children in the car might be lesslikely to respond to penalties arising from DUIpolicies. We cite from Quinlan et al. (2000):“[o]f all drivers transporting a child who died,drinking drivers were more likely than non-drinking drivers to have had a previous licensesuspension (17.1% vs. 7.1%) or conviction for

driving while intoxicated (7.9% vs. 1.2%).”8

This potentially suggests that drivers guilty ofDUI with a child passenger in the car may beparticularly strongly addicted to alcohol or maybe exceptionally prone to illegal behavior orcognitive dissonance.9 Thus, they may be lesslikely to modify their behavior in response toany law, including BAC limit laws, comparedto the average adult.

• ALR is the immediate removal of a per-son’s driver’s license when a chemical testproves the driver has exceeded the legal BAC orthe driver refuses to take a test that reveals BAC.Zador et al. (1989) found a 5% overall reduc-tion in fatal crashes as a result of ALR laws.In Ohio, ALR laws were effective in reduc-ing crash rates as much as 35% for offenderswith suspended licenses compared to offend-ers without suspended licenses (Voas, Tippetts,and Taylor, 2000). Villaveces et al. (2003) andGrabowski and Morrisey (2004, 2006) foundthat the laws reduced overall motor vehicle fatal-ities, and Grabowski and Morrisey (2004) alsofound that ALR laws reduced motor vehiclefatalities among older adolescents and youngadults. As of October 2002, 40 states and theDistrict of Columbia had adopted ALR laws(National Highway Traffic Safety Administra-tion, 2003).

• Specifically targeting the problem of youngdrinking drivers, a zero tolerance law makes itillegal for persons under the legal drinking ageof 21 to drive with any detectable alcohol intheir blood, a limit usually defined between 0.00and 0.02 BAC depending on the state. In 1995,Congress passed the National Highway SystemDesignation Act, which included a provisionrequiring all states to adopt zero tolerance lawsby 1998 or forfeit federal highway funds.10

8. Both the CDC (2004) and Quinlan et al. (2000)also found that the likelihood of a child being restraineddecreased as the driver’s BAC level increased (CDC, 1997,2004; Quinlan et al., 2000). During 1997–2002, 68% ofchild passengers who died while riding with drinking driverswere unrestrained at the time of the crash (CDC, 2004).

9. Cognitive dissonance is a psychological phenomenonthat refers to the state whereby a person feels uncomfortablewith dissonance between conflicting thoughts and thusmodifies a belief or behavior to bring the thoughts intoaccordance. For instance, in the group of drinking driversthat are more resistant to effects of law, they may resolvesuch conflicting thoughts as “It is illegal/dangerous to drivewhile intoxicated” and “I am going to drive home” byconvincing themselves that they are not drunk, that impaireddriving is not really dangerous, or that they enjoy engagingin illicit activities.

10. NHTSA. The Facts: Zero Tolerance (http://www.nhtsa.dot.gov/people/outreach/SafeSobr/17qp/zero.html).

396 CONTEMPORARY ECONOMIC POLICY

The CDC (2002) found that during the periodof 1982–2001, alcohol-related fatal crashesfell among all age groups with the largestdecrease among drivers younger than 21. Theselaws appear to have been effective in reduc-ing heavy drinking (Carpenter, 2004), alcohol-related crashes (Wagenaar and Toomey, 2002),and alcohol-related fatal crashes (Eisenberg,2003; Villaveces et al., 2003; Voas, Tippetts, andFell, 2003).

We also include selected alcohol policies thatdo not target DUI specifically but can affect theoverall availability of alcohol. These include theinflation-adjusted beer tax rates and the MLDA.We also include a proxy variable for alcoholavailability in form of the estimated percentageof state population residing in “dry” countieswhere alcohol cannot be legally purchased.11

• Beer taxes are typically the alcohol taxof choice in empirical studies because beer isthe most popular alcoholic beverage. Increasesin beer taxes have been found to be translatedinto higher beer prices within 3 mo or lessof initiation of the tax increase (Young andAgnieszka, 2002) and it has been empiricallyverified that increased prices reduce alcohol use(e.g., Coate and Grossman, 1988; Grossman,Coate, Arluck, 1987; Manning, Blumberg, andMoulton, 1995).

A number of studies have found that higherbeer taxes reduce traffic fatalities among youthand adults (examples include Chaloupka, Saf-fer, and Grossman, 1993; Ruhm, 1996; Saf-fer and Grossman, 1987). On the other hand,the validity of these findings has been chal-lenged in more recent studies like Dee (1999),Young and Likens (2000), and Dee and Evans(2001b) on the grounds that the effects wereoften implausibly large, not robust to the inclu-sion of other state policy variables, or spu-rious since they apparently reduced daytimefatalities among teen drivers rather than night-time fatalities. We explore this by estimatingadditional models that separately consider day-time and nighttime fatalities for all three agegroups.

In 1970, 33 states had an MLDA of 21yr, but between 1970 and 1975, many stateslowered those to as little as 18 yr. Starting in1977, some of these states again began rais-ing the MLDA. In 1984, the federal govern-ment passed the Uniform Drinking Age Act,

11. We are grateful to Grossman and Markowitz forsharing the data on this variable.

which denied federal highway funds to statesthat did not increase MLDA to 21 yr. By 1988,all states were in compliance. MLDA has beendescribed as the most well studied of alco-hol policies. A comprehensive review of morethan 130 high-quality peer-reviewed publishedarticles on MLDA between 1960 and 1999is provided by Wagenaar and Toomey (2002).They find that of studies analyzing the relation-ship between higher MLDA and drinking, 33%report a significant negative effect, and only onestudy reports a significant positive effect. Fifty-eight percent of studies analyzing the relation-ship between higher MLDA and motor crashesfind a significant negative relationship, and nonefinds a plausible positive relationship. Notethat, however, since there is little variation inwithin-state MLDA in the period covered byour study, there may not be enough statisticalpower to detect any effect of MLDA on fatalinjuries for CMVO even if an effect does trulyexist.

III. DATA AND METHODS

This study uses pooled cross-sectional timeseries data from all states and the District ofColumbia over 1982–2002. Data on fatal inju-ries for CMVO are obtained from the NHTSA’sFatality Analysis Reporting System (FARS),available at http://www-fars.nhtsa. dot.gov.12

FARS contains a record of all motor vehiclecrashes that occur on public roadways that resultin the death of a person within 30 d of the crash(Tessmer, 2006).

We do the analysis separately for 0- to 4-yr-olds, 5- to 9-yr-olds, and 10- to 15-yr-olds.The rationale behind this separate analysis isthat the impact of alcohol policies may differacross children who are infants or of preschoolage (0–4 yr), versus those who at least need tobe transported to and from school and possiblyother activities on a regular basis but not likelyto be driven around by peers (5–9 yr), versusthose who are likely to be driven around byslightly older peers (10–15 yr). However, wedeliberately exclude teens above 15 yr since ourfocus is on how DUI policies affect fatalities

12. We are grateful to the National Center for Statistics& Analysis’s Information Services Branch for generating aFARS report on motor vehicle occupant fatalities by state,year, and age for our analysis.

SEN & PINO: ALCOHOL POLICIES AND MOTOR VEHICLE FATALITIES FOR CHILDREN 397

TABLE 1Distribution of Fatal Injury Counts among Child Motor Vehicle Occupants, by Age Group

Number of State-Year Number of State-Year Number of State-YearCells (Percent of Sample) (%) Cells (Percent of Sample) (%) Cells (Percent of Sample) (%)

Fatal Injury Counts Age 0–4 Age 5–9 Age 10–15

0 7.38 8.22 2.051 to <10 46.40 56.86 28.5810 to <20 29.97 26.56 25.9020 to <50 12.89 7.13 37.3550 to <100 3.36 1.03 4.70100 or more 0.00 0.00 1.42

Note: N = 1, 071.

among those who are generally unlikely to bedrinking and driving themselves.13

Our sample consists of data from 1,122 state-year observations. Table 1 gives the distributionof fatal injuries for CMVO in those state-yearcells. It is seen that a very substantial numberof cells have fewer than 10 fatal injury countsfor each age group and a nontrivial number havezero fatal injuries. Hence, employing a conven-tional fatality rate ordinary least squares modelis likely to yield an imprecise fit and weak sta-tistical power, and thus a count data model ispreferred. Accordingly, we estimate a condi-tional fixed-effects Poisson model,14 where wedirectly estimate the relationship between alco-hol policies and fatal injuries among CMVO.The mean of yst in this reduced form model isgiven by:

E(yst)=δsλst =δsexp(D stα+Mstγ+Xstβ+u t ).

(1)

δs represents state fixed effects and D strepresents a vector of DUI policies in eachstate and year. Mst represents a vector of otherdriving laws not related directly to alcohol,which include speed limits on rural highways,primary and secondary seatbelt laws, child seat

13. In this context, we debated about using fatalities for10- to 14-yr-olds. But since the NHTSA uses categories 0–4,5–0, and 10–15 in its publications on child fatality rates,and we wanted our analysis to be compatible with theserates, we elected to use the same age groups.

14. We use the Poisson model rather than the negativebinomial model because some econometricians suggest thatwhen “fixed effects” are an issue, then the Poisson modelmay be preferred. However, we estimate negative binomialmodels as part of robustness checks.

laws, and booster seat laws.15,16 Xst representsalcohol policies that affect general accessibil-ity and price rather than directly applying toDUI—including the inflation-adjusted beer taxrate, the MLDA, and an estimate of the per-centage of state population residing in “dry”counties. Additionally, Xst includes the stateunemployment rate. Research by Ruhm (2000)suggests that mortality from a number of causes,including traffic fatalities, increases during timesof economic expansion and low unemployment;hence, it is possible that state unemploymentrates are correlated to fatal injuries for CMVO.u t represents a vector of binary “year effects.”The models are estimated both with and withoutthe inclusion of the variables in Xst. Finally, allmodels include the log of the state population ofchildren in the age group under consideration.

15. The NHTSA recommends that infants 0–1 yr beplaced in rear-facing seats and that infants greater than ayear and at least 20 lbs (approximately 1–4 yr) be placed infront-facing seats. All states have had some form of this lawsince 1985. The NHTSA also recommends a booster seatfor children aged 4–8 yr (until child is at least 4′9′ tall).However, in 2003, the last year of our study, only 15 stateshad any form of booster seat law and only 2 states (Maineand Wyoming) had the full booster seat law as recommendedby the NHTSA. For more information on NHTSA childrestraint recommendations, visit http://www.nhtsa.dot.gov/and search for “General Child Seat Use Information.”

16. One motor vehicle policy that we do not explicitlycontrol for is graduated driver’s licensing laws, whichrequire new 15- to 17-yr-old drivers to advance throughrestrictive beginner and intermediate phases before they canachieve full licensure. These laws have been associatedwith reductions in fatalities among 15- to 17-yr-olds (Dee,Grabowski, and Morrisey, 2005; Morrisey et al., 2006), butno spillover effects have been detected for fatalities amongolder teens or young adults (Dee, Grabowski, and Morrisey,2005); hence, there is little reason to assume that these lawswill significantly affect fatalities among infants and youngchildren.

398 CONTEMPORARY ECONOMIC POLICY

This permits interpreting the coefficient esti-mates as changes in “fatality rates” as well as“fatality counts,” and we use both these termsintermittently when discussing the results.

IV. RESULTS AND DISCUSSION

Table 2 presents descriptive statistics for allthe above variables.

Before estimating the reduced form modeldescribed in Equation (1), we present resultsfrom conditional maximum likelihood Poissonmodels that verify the existence of a directcorrelation between fatal injuries for CMVOand alcohol prevalence. Table 3 shows theseestimation results, where alcohol prevalence ismeasured by apparent per capita alcohol usein gallons per year for each state-year cell.The National Institute of Alcohol Use andAlcoholism calculates this variable based onannual sales of alcohol in the state and the

state population. Results are presented in theexponentiated form, Exp (β), where the defaultvalue is 1 or Exp (0). Semielasticities—namely,the percentage change in the dependent vari-able associated with a one-unit increase inthe independent variable—can be calculated as100(Exp (β) − 1).

We find that alcohol prevalence is stronglycorrelated with fatal injuries for CMVO forall three age groups. Specifically, a one-gallonincrease in apparent per capita alcohol use(which, at the sample mean of 2.44, representsa 41% increase in this variable) is associatedwith average increases of 64% of fatal injuryamong children aged 0–4, 55% among childrenaged 5–9, and 38% among children aged 10–15.The corresponding elasticities for the three agegroups, calculated at the sample mean, arerespectively 1.56, 1.34, and 0.80. This tenta-tively suggests that younger children are morevulnerable to dying in a motor vehicle crash than

TABLE 2Variable Descriptions, Sample Means, and Standard Deviations

StandardVariable Description N Mean Deviation

Fatal injuries for CMVO, 0–4 yr FARS motor vehicle occupant fatality count,for age 0–4

1,071 11.90 13.59

Daytime 1,071 7.40 8.21Nighttime 1,071 4.45 5.84

Fatal injuries for CMVO, 5–9 yr FARS motor vehicle occupant fatality count,for age 5–9

1,071 8.71 9.51

Daytime 1,071 5.41 5.65Nighttime 1,071 3.27 4.47

Fatal injuries for CMVO, 10–15 yr FARS motor vehicle occupant fatality count,for age 10–15

1,071 21.23 19.98

Daytime 1,071 10.89 10.08Nighttime 1,071 10.34 10.60

Apparent per capital alcohol use Apparent per capita ethanol consumption ingallons per year

1,071 2.44 0.63

0.08 BAC law 1 if illegal per se at 0.08 BAC law in effect 1,071 0.17 0.370.10 BAC law 1 if illegal per se at 0.10 BAC law in effect 1,071 0.70 0.44Zero tolerance law 1 if zero tolerance for underage DUI law in effect 1,071 0.43 0.48Per se ALR 1 if per se ALR law 1,071 0.57 0.48Primary seatbelt 1 if primary enforcement seatbelt law in effect 1,071 0.22 0.42Secondary seatbelt 1 if secondary enforcement seatbelt law in effect 1,071 0.48 0.50Rural speed limit Speed limit (actual miles) on rural highways 1,071 63.07 6.27Booster seat law 1 if booster seat law in effect 1,071 0.007 0.077Child seat law 1 if child seat law in effect 1,071 0.92 0.25Beer tax rate Inflation-adjusted per gallon beer tax in dollars

per gallon (federal + state)1,065 0.73 0.25

MLDA Minimum legal drinking age 1,071 20.68 0.81Percent in dry county Percent of population (estimated) in dry counties 1,071 4.11 9.55Unemployment rate State-level unemployment rate 1,071 5.95 2.16

SEN & PINO: ALCOHOL POLICIES AND MOTOR VEHICLE FATALITIES FOR CHILDREN 399

TABLE 3Conditional Fixed-Effects Poisson Model Results for Relationship between Alcohol Prevalence and

Fatal Injury among CMVO

Motor VehicleOccupant, Exp (β) (p Value)

Variable Age 0–4 Age 5–9 Age 10–15

Apparent per capita alcohol use 1.5394∗∗(.00) [1.56] 1.6010∗∗(.00) [1.34] 1.3340∗∗(.00) [0.80]Primary seatbelt 0.8582∗∗(.00) 0.8648∗∗(.02) 0.9070∗∗(.01)Secondary seatbelt 1.0204 (.64) 0.9293 (.15) 0.9600 (.24)Child seat law 0.9921 (.91) 1.0120 (.89) 1.0285 (.80)Booster seat law 0.8581 (.38) 0.6442∗∗(.04) 1.1157 (.42)Rural speed limit 1.0064 (.12) 1.0041 (.38) 1.0064∗(.09)Unemployment rate 0.9813∗(.07) 0.9733∗∗(.03) 0.9718∗∗(.01)N 1,071 1,071 1,071Log likelihood −2,982.3561 −2,623.8481 −2,840.8082Wald χ2 276.08 104.83 435.35

Notes: Models are estimated using a conditional fixed-effects Poisson method. All models also contain a vector of yeardummies and the log of the population of children in that age group for the state-year cell. Elasticities of fatal injury rateswith respect to per capita alcohol use are presented in square brackets. They are calculated as {(Exp(β) − 1)}/{1/Xmean},where Xmean is the sample mean of the independent variable.

∗p < 0.10; ∗∗p < .05.

older children when alcohol prevalence at thestate level increases.

Table 4 presents results from estimating theeffects of alcohol policies on fatal injuries forCMVO, both with and without the variablesin Xst.. In specifications that exclude thesevariables, presence of BAC limit laws of 0.08and 0.10 both appear to reduce fatal injuriesfor CMVO among the 0–4 age group by 12.5%and 8.5%, respectively, though the latter is onlymarginally significant. The BAC limit laws donot appear to have any significant effects forthe two other age groups. However, per se ALRlaws seem to reduce motor vehicle fatalities forall three age groups, by 8.5%, 13.2%, and 4.5%,respectively, though it is only weakly significantfor 10- to 15-yr-olds.

In specifications where variables from Xstare included, the most notable change fromthe earlier results is that BAC limit laws nowcease to be significant for 0- to 4-yr-olds,while continuing to remain insignificant for theother two age groups. The ALR laws continueto have significant effects with reductions infatalities of 6.7% and 11.2% for the 0–4 and5–9 yr age groups, respectively, and a reductionof 2.2% for 10- to 15-yr-olds, though this resultnow falls just short of the 10% level of signif-icance. We also estimated an additional modelspecification where we included interactions ofthe BAC limit laws and zero tolerance laws with

ALR. The purpose of this article was to explorewhether, in accordance with studies like Dee andEvans (2001a), BAC limit laws were significantwhen they were in effect in conjunction with theALR laws. However, the coefficient estimatesof the interacted terms continued to be statis-tically insignificant for all age groups. Theseresults are available upon request. In light ofthe (previously cited) findings by Quinlan et al.(2000) that drinking drivers who were transport-ing a child who then died in a crash were morelikely to have previous license suspensions andDUI convictions than their nondrinking counter-parts, we conjecture that those drivers who drinkand drive with child passengers may be particu-larly strongly addicted to alcohol or have othercognitive and behavioral issues that make themunresponsive to existence of BAC limit laws.It may also be conjectured that ALR laws arerelatively more effective because they actuallykeep such drivers off the street ex post factorather than merely through a deterrence effect.These are, however, mere speculations—andtargeted microlevel studies are called for to ver-ify whether this is indeed the case.

Among the variables in Xst not directlyrelated to alcohol, higher speed limits on ruralhighways are associated with more fatal injuriesamong 0- to 4-yr-olds and 10- to 15-yr-olds.On average, a 10-mile increase in such speedlimits appears to increase fatal injuries by about

400 CONTEMPORARY ECONOMIC POLICY

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SEN & PINO: ALCOHOL POLICIES AND MOTOR VEHICLE FATALITIES FOR CHILDREN 401

7%. While the average effects for 5- to 9-yr-olds are of a similar magnitude, the resultsare more imprecise and fall short of statisticalsignificance at even the 10% level. Enforce-ment of primary seatbelt laws is associated withan approximately 15% decline in fatal injuryamong 0- to 4-yr-olds and 5- to 9-yr-olds, butwith no significant results in case of 10- to15-yr-olds. While initially it seems implausiblethat primary seatbelt laws would influence fatalinjury rates among 0- to 4-yr-olds, it shouldbe noted that, over the period under study,numerous states have permitted adult safetybelt restraints for young children—as long asthey met certain state-specified height and/orweight requirements. On a related note, whilethe presence of child safety seat laws per sedid not appear to significantly reduce fatali-ties among CMVO, the booster seat laws didappear to reduce fatalities among 5- to 9-yr-olds by an average of 30%, even though theresults were only marginally significant. Thisis interesting, and perhaps unexpected, givenhow little variation there is in this law in ourdata set. Nonetheless, the fact that booster seatlaws are found to be associated with reducedfatalities among 5- to 9-yr-olds—but not 0- to4-yr-olds or 10- to 15-yr-olds—suggests thatthese results are not spurious (recall that exist-ing booster seat laws apply to children 4- to8-yr-old). Further research focusing primarily onbooster seat laws is recommended to verify theseresults. Finally, in accordance with the findingsof Ruhm (2000) that times of low unemploy-ment and economic expansions are also asso-ciated with increases in many undesirable phe-nomena, including increases in mortality froma variety of causes, we find that lower (higher)unemployment rates are associated with more(fewer) fatal injuries among CMVO. Specif-ically, a 1 percentage point increase in thestate unemployment rate appears to reduce suchfatal injuries on average by about 3%–4%for the three age groups. Our findings withrespect to speed limits, primary seatbelt laws,and the state unemployment rate are generallyconsistent with results from extant studies byGrabowski and Morrisey (2004, 2006, 2007)about how these variables affect overall motorvehicle fatalities or fatalities among specific agegroups like older adolescents.

Of the variables in Xst that pertain to alcoholand alcohol-related policy, the MLDA and theestimated percent of population living in drycounties do not have any statistically significant

relationship with fatal injuries among CMVO.17

Higher beer tax rates, however, appear to reducesuch fatal injuries among all three age groups,with estimated elasticities (calculated at thesample mean of beer taxes) ranging from −0.18for 10- to 15-yr-olds to −0.28 for 0- to 4-yr-olds. We note that our elasticities are smallerthan the estimated elasticities for 16- to 19-yr-olds that were found by Dee and Evans (2001a).They are, however, higher than the elasticitiesof −0.11 to −0.15 that Ruhm found for theoverall population. It should also be notedthat, given that beer tax rates constitute only asmall fraction of beer prices—about 10%, bysome studies’ estimates (e.g., Dee, 1999)—thistranslates into the elasticity of fatal injurieswith respect to beer prices ranging between−1.18 and −2.28. These estimates seem onthe high side, especially in context of findingsregarding price elasticity of alcohol by Manning,Blumberg, and Moulton (1995) where the mostprice-responsive group of drinkers had a priceelasticity of −1.19. On the other hand, givenhow low the fatal injury counts are for theage groups included in this study, very smallchanges in the absolute number of fatalities cantranslate into quite large percentage changes,and that may, in part, account for these results.

Dee and Evans (2001a) had also expressedconcern that the results pertaining to beer taxesand teen motor vehicle fatalities may be spu-rious because, in their study, the estimatedeffects of beer taxes appeared to be higher forteen motor vehicle fatalities occurring duringthe day than those occurring at night, eventhough alcohol-related crashes were more likelyto occur at night. To examine whether a sim-ilar phenomenon occurs for children as well,we reestimate Equation (1) using as our newdependent variable the count of fatalities thatoccur during the day (6 a.m. to 6 p.m.) andthose that occur during night (6 p.m. to 6 a.m.)separately for the three age groups. We look atthe relationship of daytime and nighttime fatal-ities with alcohol prevalence as well as alcoholpolicies. One issue with this analysis is thatthe number of state-year cells with 0 fatali-ties as well as less than 10 fatalities is now

17. We caution that this might simply be due to lack ofvariation in MLDA in our data, as most states had raisedit to 21 yr by the early 1980s, and all states had done soby 1988. On the other hand, we note that Dee and Evans(2001a, 2001b) used data over a similar period and foundthat changes in MLDA affected motor vehicle fatalitiesamong older adolescents in the expected direction.

402 CONTEMPORARY ECONOMIC POLICY

quite large, especially for 0- to 4-yr-olds and5- to 9-yr-olds (for nighttime fatalities, e.g.,91.8% and 95.4% of cells have 10 or fewerfatalities), which may lead to loss of statisti-cal power and the ability to estimate resultswith precision. Nonetheless, it is of interest tosee how the magnitudes of the estimated effectsof beer taxes on daytime and nighttime fatali-ties compare.

The results for daytime and nighttime fatali-ties are presented in Table 5. For economy ofspace, results pertaining to other traffic poli-cies (like speed limits and seatbelt laws) areomitted and are available upon request. The esti-mated relationship between daytime and night-time fatalities and alcohol prevalence is seen todiffer across the three age groups. While alco-hol prevalence is very significantly associatedwith both daytime and nighttime fatalities, themagnitude of the relationship is larger in caseof nighttime fatalities for 0- to 4-yr-olds and10- to 15-yr-olds, with respective elasticities of1.51 and 0.90 for nighttime fatalities versus 1.00and 0.68 for daytime fatalities, but for 5- to9-yr-olds the relative magnitudes are reversed,with the elasticity of nighttime fatalities being0.76 and daytime fatalities being 2.12. Congru-ently, higher beer taxes have larger and morestatistically significant effects on nighttime fatal-ities for 0- to 4-yr-olds and 10- to 15-yr-olds;while for 5- to 9-yr-olds, higher beer taxes havelarger and more statistically significant effectson daytime fatalities. It is not immediately obvi-ous why there should be such differing effectsacross the age groups. However, it is clear thatfor 0- to 4-yr-olds and 10- to 15-yr-olds, theconcern raised by Dee and Evans (2001a) aboutthe “validity” of beer tax results does not apply.While beer taxes appear to affect daytime ratherthan nighttime fatalities for 5- to 9-yr-olds, giventhe congruence in the patterns of effects of alco-hol prevalence and effects of beer taxes, there islittle ground for assuming that these results arespurious.18 Finally, we also note that the general

18. We again remind readers that the baseline fatalitycounts for these age groups are very low, and they are thelowest for 5- to 9-yr-olds. Thus, a fairly small change infatality counts can translate into a fairly large and significantpercentage change in fatalities. For example, the largestnighttime elasticity of fatalities with respect to beer taxesis −0.36 (for 0- to 4-yr-olds). This indicates that a 100%increase in beer taxes will reduce fatalities by 36%—sincethe pooled state-year sample mean of nighttime fatalitiesfor this age group is 4.45, this translates into an averagereduction of 1.6 in actual number of fatalities in a state andyear. Similarly, the largest daytime elasticity of fatalities

result that higher beer taxes reduce child fatalinjuries is consistent with previous findings bySen (2006) that higher beer taxes reduced childfatalities due to homicide.

We reestimated all the above models usingconditional fixed-effects negative binomial met-hods, and the results were very similar. They areavailable upon request.

Finally, we acknowledge that our study suf-fers from two problems which are inherent in allextant studies in the literature on motor vehiclefatalities and DUI and other alcohol policies.The first of these is that although the mod-els account for time-invariant state-level char-acteristics as well as year-level characteristics,there may remain other unobservable factorsthat are state specific and time variant thatmay confound the relationship between the poli-cies and the outcome variable. We reestimatedthe models after including state dummies inter-acted with the time trend, and in those models,we found that ALR laws and beer tax ratesno longer had negative and significant effects;indeed there was a counterintuitive positive signon the tax effect for 10- to 15-yr-olds. How-ever, it is not clear whether these changes occurdue to removal of bias from unobservables orwhether the addition of more than 50 other vari-ables result in “noise” and loss of statisticalpower. Furthermore, the state trends can onlycontrol for those unobservables that change ina linear fashion within each state. The idealmethod to counter the presence of unobservableswould be if we could identify a certain demo-graphic group for whom motor vehicle fatali-ties are unrelated to alcohol policies and thenuse that data in conjunction with a difference-in-difference-in-difference type model. In prac-tice, we are unaware of the existence of anysuch demographic group. The second of theproblems is the possibility that DUI and otheralcohol policies are endogenous—specifically,they are implemented in response to a sud-den increase in motor vehicle fatality rateswithin the state. The use of standard fixed-effects methods do not adequately address thisissue. What would be required are variables thatperform as viable instruments—namely, theywill be strongly correlated with the policies but

with respect to beer taxes is −0.19 (for 5- to 9-yr-olds).This indicates that a 100% increase in beer taxes will reducefatalities by 19%—and since the pooled state-year samplemean of daytime fatalities for this age group is 5.41, thistranslates into an average reduction of about one fatality ina state and year.

SEN & PINO: ALCOHOL POLICIES AND MOTOR VEHICLE FATALITIES FOR CHILDREN 403

TA

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∗ p<

.10;

∗∗p

<.0

5.

404 CONTEMPORARY ECONOMIC POLICY

not correlated with factors that may directlyaffect motor vehicle fatality rates. Again, weare not aware of any available variables thatwould feasibly satisfy those conditions. In lightof these problems, it may be argued that theresults on alcohol policies and fatalities amongCMVO that we present in this article should betreated more as “associative” relationships ratherthan decisively asserting causality.

V. CONCLUSIONS

This study adds to the substantial literature onalcohol policies and motor vehicle fatalities byexploring the relationship between such policiesand motor vehicle fatalities among childrenunder driving age. Results indicate that ALRlaws and higher beer tax rates reduce fatalitiesfor all young children. Zero tolerance laws andBAC limit laws do not appear to have significanteffects. Among the other motor vehicle policiesused as control variables, primary seatbelt laws,rural highway speed limits, and booster seat lawsaffect fatalities for all or some of the three agegroups considered.

While we have mentioned the caveats thatprevent us from establishing definitive causalitybetween alcohol policies and child motor vehiclefatalities, a brief discussion of possible policyimplications of this study seems appropriate.Since motor vehicle crashes are the leadingcause of death among children younger than15 yr, a clear imperative exists for formulationof policies that help reduce such deaths. Thisstudy shows a strong correlation between theprevalence of alcohol at the state level and anincrease in such deaths. This study also indicatesthat increasing beer taxes can help reduce suchdeaths. Manning et al. (1989) argue that alcoholtaxes are not sufficient to cover the social coststhat alcohol abusers impose on others and thatthe taxes should be increased by more than100%. Average inflation-adjusted beer taxes (thesum of state and federal) have actually fallensince the publication of that article, from $0.67per gallon in 1989 to $0.46 per gallon in2002. This is primarily driven by declines instate beer taxes in real terms: 23 states havenot raised their nominal per gallon beer taxrates in the past two decades. Thus, one canmake a strong case for increasing these taxessubstantially.

With regard to DUI policies, all states havealready adopted zero tolerance DUI laws fordrivers younger than 21 yr. However, it is not

clear whether there will be added benefits toadopting the suggestion by Li (2000) of imple-menting zero tolerance DUI laws for all drivers,or the suggestion by Quinlan et al. (2000) ofimposing stricter BAC limit laws specifically fordrivers with child passengers, since the extantlaws seem to have little effect on child motorvehicle fatalities. However, one possibility is toexplore more stringent ALR laws for drinkingdrivers who are transporting children, includinglonger periods of license suspension.

Finally, this study found indications thatone of the relatively new driving policies (notpertaining to alcohol)—namely, booster seatlaws, may be effective in reducing child motorvehicle fatalities. We plan to explore this furtherin future research.

REFERENCES

Apsler, R., A. R. Char, M. W. Harding, Rainbow Tech-nology, and T. M. Klein. “The Effects of 0.08 BACLaws.” NHTSA, March 1999, DOT HS 808 892, 1999.

Borkenstein, R. F., R. F. Crowther, R. P. Shumate, W.B. Ziel, and R. Zylman. “The Role of the DrinkingDriver in Traffic Accidents.” Bloomington, Indiana:Department of Police Administration, Indiana Univer-sity, 1964.

Carpenter, C. “How Do Zero Tolerance Drunk DrivingLaws Work?” Journal of Health Economics, 23, 2004,61–83.

CDC. “Alcohol-Related Traffic Fatalities Involving Chil-dren—United States, 1985–1996.” Morbidity andMortality Weekly Report, 46, 1997, 1130–33.

. “Involvement by Young Drivers in Fatal Alcohol-Related Motor-Vehicle Crashes—United States,1982–2001.” Morbidity and Mortality Weekly Report,51, 2002, 1089–91.

“Child Passenger Deaths Involving DrinkingDrivers—United States, 1997–2002.” Morbidity andMortality Weekly Report, 53, 2004, 77–79.

Chaloupka, F. J., H. Saffer, and M. Grossman. “AlcoholControl Policies and Motor-Vehicle Fatalities.” Journalof Legal Studies, 22, 1993, 161–86.

Coate, D., and M. Grossman. “Effects of Alcoholic BeveragePrices and Legal Drinking on Youth Alcohol Use.”Journal of Law and Economics, 31, 1988, 145–71.

Dee, T. S. “State Alcohol Policies, Teen Drinking and TrafficFatalities.” Journal of Public Economics, 72, 1999,289–315.

. “Does Setting Limits Save Lives? The Case of0.08 BAC Laws.” Journal of Policy Analysis andManagement, 20, 2001, 113–30.

Dee, T. S., and W. N. Evans. “Teens and Traffic Safety” inAn Economic Analysis of Risky Behavior Among Youth,edited by J. Gruber. Chicago: University of ChicagoPress, 2001a, 121–65.

. “Behavioral Policy and Teen Traffic Safety.” AEAPapers and Proceedings, 91, 2001b, 90–96.

Dee, T. S., D. C. Grabowski, and M. A. Morrisey. “Grad-uated Driver Licensing and Teen Traffic Fatalities.”Journal of Health Economics, 24, 2005, 571–89.

Eisenberg, D. “Evaluating the Effectiveness of PoliciesRelated to Drunk Driving.” Journal of Policy Analysisand Management, 22, 2003, 249–74.

SEN & PINO: ALCOHOL POLICIES AND MOTOR VEHICLE FATALITIES FOR CHILDREN 405

Foss, R. D., J. R. Stewart, and D. W. Reinfurt. “Evaluationof the Effects of North Carolina’s 0.08% BAC Law.”Accident Analysis and Prevention, 33, 2001, 507–17.

Grabowski, D. C., and M. A. Morrisey. “Gasoline Prices andMotor Vehicle Fatalities.” Journal of Policy Analysisand Management, 23, 2004, 575–93.

. “Do Higher Gasoline Taxes Save Lives?” Eco-nomics Letters, 90, 2006, 51–55.

. “System-Wide Implications of the Repeal of theNational Maximum Speed Limit.” Accident Analysisand Prevention, 39, 2007, 180–89.

Grossman, M., D. Coate, and G. Arluck. “Price Sensitivityof Alcoholic Beverages in the United States,” inControl Issues in Alcohol Abuse Prevention: Strategiesfor Communities, edited by H. D. Holder. Washington,DC: JAI Press, 1987, 169–98.

Hingson, R., T. Heeren, and M. Winter. “Effects of Recent0.08% Legal Blood Alcohol Limits on Fatal CrashInvolvement.” Injury Prevention, 6, 2000, 109–14.

Li, G. “Child Injuries and Fatalities from Alcohol-RelatedMotor Vehicle Crashes: Call for a Zero-TolerancePolicy.” JAMA 2000, 283, 2249–52.

Manning, W. G., L. Blumberg, and L. H. Moulton.“The Demand for Alcohol: The Differential Responseto Price.” Journal of Health Economics, 14, 1995,123–48.

Manning, W. G., E. B. Keeler, J. P. Newhouse, E. M. Sloss,and J. Wasserman. “The Taxes of Sin: Do Smokers andDrinkers Pay their Way?” JAMA, 261, 1989, 1604–09.

Margolis, L. H., R. D. Foss, and W. G. Tolbert. “Alcoholand Motor Vehicle-Related Deaths of Children asPassengers, Pedestrians, and Bicyclists.” JAMA, 283,2000, 2245–48.

Morrisey, M. A., and D. C. Grabowski. “State Motor VehicleLaws and Older Drivers.” Health Economics, 14, 2005,407–19.

Morrisey, M. A., D. C. Grabowski, T. S. Dee, and C.Campbell. “The Strength of Graduated Drivers LicensePrograms and Fatalities Among Teen Drivers andPassengers.” Accident Analysis and Prevention, 38,2006, 135–41.

Moskowitz, H., and M. Burns. “Effects of Alcohol onDriving Performance.” Alcohol Health and ResearchWorld, 14, 1990, 12–14.

National Highway Traffic Safety Administration, U.S. De-partment of Transportation. “Administrative LicenseReview (Suspension).” Traffic Safety Facts: Laws,1(1), May 2003. http://www.nhtsa.dot.gov/people/injury/New-fact-sheet03AdminLicenseRevoctn.pdf.

. “Legislative History of .08 Per Se Laws, FinalReport.” July 2001. DOT HS 809 286. 2006., AccessedDecember 28, 2006. http://www.nhtsa.dot.gov/people/injury/research/pub/alcohollaws/08History/index.htm#CONTENTS.

Quinlan, K. P., R. D. Brewer, D. A. Sleet, and A. M.Dellinger. “Characteristics of Child Passenger Deaths

and Injuries Involving Drinking Drivers.” JAMA, 2000,283, 2249–52.

Ruhm, C. J. “Alcohol Policies and Highway Vehicle Fatali-ties.” Journal of Health Economics, 15, 1996, 435–54.

. “Are Recessions Good for Your Health?” QuarterlyJournal of Economics, 115, 2000, 617–50.

Saffer, H., and M. Grossman. “Drinking Age Laws andHighway Mortality Rates: Cause and Effect.” Eco-nomic Inquiry, 1987, 25, 403–17.

Sen, B. “The Relationship between Beer Taxes, Other Alco-hol Policies and Child Homicide Deaths.” Topics inEconomic Analysis & Policy, [B. E. Journals in Eco-nomic Analysis & Policy], 6, 2006. Accessed October2008. http://www.bepress.com/bejeap/topics/vol6/iss1/art15.

Tessmer, Joseph M. FARS Analytic Reference Guide2006, Washington, DC: U.S. Department of Trans-portation, National Highway Traffic Safety Admin-istration, 2006. Accessed December 18, 2006.ftp://ftp.nhtsa.dot.gov/FARS/FARS-DOC/FARS06.pdf.

Villaveces, A., P. Cummings, T. D. Koepsell, F. P. Rivara, T.Lumley, and J. Moffat. “Association of Alcohol-relatedLaws with Deaths due to Motor Vehicle and Motorcy-cle Crashes in the United States, 1980–1997.” Ameri-can Journal of Epidemiology, 157, 2003, 130–40.

Voas, R. B., A. S. Tippetts, and J. Fell. “The Relationshipof Alcohol Safety Laws to Drinking Drivers in FatalCrashes.” Accident Analysis and Prevention, 32, 2000,483–92.

Voas, R. B., A. S. Tippetts, and J. C. Fell. “Assessing theEffectiveness of Minimum Legal Drinking Age andZero Tolerance Laws in the United States.” AccidentAnalysis and Prevention, 35, 2003, 579–87.

Voas, R. B., A. S. Tippetts, E. Taylor. Effectiveness ofthe Ohio Vehicle Action and Administrative LicenseSuspension Laws. Washington, DC: U.S. Departmentof Transportation, National Highway Traffic SafetyAdministration, 2000., Accessed January 2000.http://www.nhtsa.dot.gov/people/injury/research/ohio/toc.html.

Wagenaar, A. C., and T. L. Toomey. “Effects of MinimumDrinking Age Laws: Review and Analyses of theLiterature from 1960 to 2000.” Journal of Studies onAlcohol, (14), 2002, 206–25. Accessed June 2007.http://www.collegedrinkingprevention.gov/SupportingResearch/Journal/wagenaar.aspx.

Young, D. J. and B. K. Agnieszka. “Alcohol Taxes andBeverage Prices.” National Tax Journal, 55, 2002,57–73.

Young, D. J., and T. W. Likens. “Alcohol Regulationand Auto Fatalities.” International Review of Law andEconomics, 20, 2000, 107–26.

Zador, P. L., A. K. Lund, M. Fields, and K. Weinberg. “FatalCrash Involvement and Laws against Alcohol-impairedDriving.” Journal of Public Health Policy, 10, 1989,367–485.