This study examines whether increasing alcohol taxes through beer, wine, and liquor taxes reduces underage drunk driving fatalities. The study uses data on alcohol taxes, alcohol consumption rates, miles driven adjusted for population, and percentages of total fatalities from drunk driving that involve those under 21 for each US state. Through multivariate regression analysis, the study finds some evidence that higher beer and wine taxes are associated with slightly lower percentages of underage drunk driving fatalities, but the results are not statistically significant. Adding liquor tax data to the model does not meaningfully change the results. Overall, the study finds limited evidence that higher alcohol taxes may help reduce underage drunk driving deaths.

1. One Too Many Red Solo Cups!
2015
DOES A BEER TAX REDUCE YOUTH DRUNK DRIVING FATALITIES
BY: TYLER COLLINS

2. 1
Abstract
If the cost of alcohol reduces the consumption of the beverage, does a hike in the price of
alcohol, caused by an alcohol tax reduce the drunk driving fatalities? This paper explores the
origins of alcohol control and touches on the different aspects of prevention. Special
consideration is given to how alcohol policies effect underage alcohol driving fatalities.

3. 2
Introduction
“Alcohol intoxication increases the risk of injury resulting from motor vehicle crashes
and violent assaults.” (Holder, et al. (2000) Every year, thousands of people die in motor vehicle
crashes and a substantial portion of those accidents are alcohol related. Since before prohibition,
the government and citizens have grappled with how to manage a substance that is infamously
difficult to manage.
Citizen advocacy groups such as, “MADD (Mothers Against Drunk Driving), RID
(Remove Intoxicated Drivers), SADD (Students Against Drunk Driving), and others launched
grassroots campaigns against alcohol-impaired driving in the late 1970s and early 1980s”
(Roizen, 2004, p. 68). Since that time, the knowledge surrounding alcohol and how it affects our
everyday lives has changed exponentially. The marketing campaigns that focused largely on
alcoholics have refocused their efforts to all consumers. “Alcohol problems arise, not from a
small group of chronic dependents, but from the drinking habits of the general population”
(Moore & Gerstein, 1981, p. 13).
Not all drinkers are the same; however, “Alcohol's effect on individuals stems from a
variety of cognitive, biological, and social factors. The propensity to binge drink may arise from
a combination of these factors, which could contribute to the underlying “cause” of binge
drinking” (Courtney & Polich, 2009). With all of these factors in play, it is only logical that to
combat the misuse of alcohol, policy makers must find a way to control the behavior of drinkers
across a broad spectrum of personal qualities.
“The most fundamental law of economics links the price of a product to the demand for
that product. Accordingly, increases in the monetary price of alcohol (i.e., through tax increases)

4. 3
would be expected to lower alcohol consumption and its adverse consequences” (Chaloupka,
Grossman, & Saffer, 2002, para. 1). Approaching alcohol consumption with this logic, “the study
found consistent evidence that increases in the price of alcohol resulting from higher monetary
prices significantly reduced the number of alcoholic drinks consumed by young adults in the past
year. Moreover, the analyses provided strong evidence that drinking in this age group is
addictive in the sense that a strong interdependency existed among past, current, and future
alcohol consumption” (Chaloupka, Grossman, & Saffer, 2002, para.2).
Purpose of the Study
“Alcohol policy is one of the severest tests of government’s will to serve the public
interest” (Stockwell, 2004, p. 1090). With alcohol affecting violent crime, personal health, and a
flood of drunk-driving deaths, it is only natural that the government and public interest groups
will try to work for the common good. According to Hanssens & Ornsteing (1985), “Alcohol
control laws can be divided into three general categories: (1) economic legislation directed at
raising revenues for the state and/or protecting sellers from competition, (2) attempts to control
the social costs resulting from excessive drinking, and (3) attempts to prevent product
adulteration and false advertising” (p. 201). This study is going to focus on the first category,
economic legislation. “Studies suggest that increases in federal or state excise taxes on alcohol
discourage heavy drinking and reduce motor vehicle fatalities” (Brown, Jewell, and Richer,
1996, p. 1043).
Background Literature
Robert Reynolds 1984 paper, “Toward the Prevention of Alcohol Problems Government,
Business and Community Action” talks about the three aspects of prevention. “The first was to
affect the terms and conditions under which alcohol is available, through special taxes, minimum

5. 4
age requirements, regulation of outlets and availability and times of sale-all the things that
determine how easy and convenient it is for people to have access to alcohol” (Reynolds, 1984,
p. 3). This paper focuses on the aspect of prevention in regard of special taxes. “The second idea
was to shape drinking practices directly by talking to people about what constitutes safe and
appropriate drinking behavior” (Reynolds, 1984, 3). “The third idea was to make the
environment a safer one in which to be drunk” (Reynolds, 1984, 3). This might include
suggestions like making for sure taxi services are available.
Reynolds’ aspects of prevention concur with other academics in this field, especially
when businesses are part of the prevention of alcohol misuse. Levine & Reinarman’s paper,
From Prohibition to Regulation: Lessons from Alcohol Policy for Drug Policy states,
Under alcohol control, all establishments licensed for on-premises consumption of
spirits were specifically restricted in ways that shaped the cultural practice of
drinking. In some areas, control laws attempted to moderate the effects of
drinking by encouraging food consumption (just as hosts of cocktail parties
served hors d’oeuvres). For example, spirit sales often were limited to bona fide
restaurants with laws specifying how many feet of kitchen space and how many
food preparation workers there must be. Most states established restrictions on the
number of entrances and their locations (back entrances are usually prohibited);
the times of day and days of the week when sales may occur; permissible
decorations; degree of visibility of the interior from the street; numbers and uses
of other rooms; distance of the establishment from churches, schools, and other
alcohol outlets; whether customers may sit at a long bar- a counter in close

6. 5
proximity to the source of alcohol- or whether they must sit at tables and order
drinks as one orders food; and the ratio of chair seating to bar seating. (Levine &
Reinarman, 1991, p. 479)
Many of these laws, frequently referred to as “Blue Laws,” shape the way people
consume alcohol. Over the years, the effectiveness of certain Blue Laws have been called into
question over their effectiveness and frustrated many who see Blue Laws as the influence the
church has over the state. But, these only account for a small portion of what influences drinking
behavior. “The number of alcohol-related driving accidents is directly related to the number of
miles driven under the influence of alcohol, which depends on: (i) the amount of alcohol
consumed; (ii) the travel distance required to obtain the alcohol; (iii) where the alcohol is
consumed; and (iv) what type of alcohol is consumed” (Baughman, Conlin, Conlin, & Pepper,
2000, p. 6).
Hypothesis
This paper’s theoretical derived hypothesis comes from an “increases in the price of
alcohol resulting from higher monetary prices significantly reduced the number of alcoholic
drinks consumed by young adults” (Chaloupka, Grossman, & Saffer, 2002, para. 2).
Method
The data for this paper is gathered from multiple sources. State level data regarding drunk
driving is gathered from (Responsibility.org). This source gives the percentage of total fatalities
in the state from drunk-driving automobile accidents divided by all automobile fatalities
(PERCTFATAL) and the percentage of total under 21 fatalities in the state from drunk-driving
automobile accidents, divided by all under 21 automobile fatalities (PERCT21). The data can be

7. 6
viewed in the form of a sitemap which draws on data from the Center for Disease Control and
Prevention.
State level data for consumption comes from (State-Specific Alcohol Consumption Rates
for 2013). The data includes, “State-Specific Weighted Prevalence Estimates of Alcohol Use and
Binge Drinking Among Women 18–44 Years of Age.” The code for any use is (ANYDRK) and
the code for binge drinking rates is (BINGE). Any use is defined as “any drink within the past 30
days” and binge drinking is defined as “4 or more drinks at any given time during the last 30
days.”
State level data for the taxes of alcohol come from The Tax Policy Center (Alcohol Rates
2000-2010, 2013-2015). The variables are divided into three categories, beer tax (BEERTAX),
wine tax (WINETAX), and liquor tax (LIQTAX). The variables reflect the dollar amount of tax
specified by beverage.
Finally, the paper uses state level data to get the number of miles driven a year in each
state and the population of each state to get the total miles driven adjusted for population by
state. To do this, the number of miles driven each year is illustrated per billion and gathered from
the United States Census (State and Local Areas, 2010) and is divided by the population of each
state, which is gathered from the United States Census (Quick Facts, 2010) to give us the new
variable of the population adjusted miles driven coded as (WEIGHTMILES).

8. 7
Design and Procedures
This paper uses a cross-sectional design across all 50 states and the District of Columbia.
The dependent variables used are (BINGE), (ANYDRK), (PERCTFATAL), and (PERCT21).
The independent variables used are (BEERTAX), (WINETAX), (LIQUORTAX), and
(WEIGHTMILES). The procedure used is a multivariate regression analysis.
Results
Table 1A
Model Summary
Model R R Square
Adjusted R
Square
Std. Error of
the Estimate
1 .298a .089 .025 .133126
a. Predictors: (Constant), WEIGHTMILES, BEERTAX,
WINETAX
Table 1B
ANOVAa
Model
Sum of
Squares df
Mean
Square F Sig.
1 Regression .074 3 .025 1.398 .256b
Residual .762 43 .018
Total .836 46
a. Dependent Variable: PERCT21
b. Predictors: (Constant), WEIGHTMILES, BEERTAX, WINETAX
Table 1C

9. 8
Table 2A (This set of tables measure PERCT21 just like Table 1 but includes the LIQTAX
Model Summary
Model R R Square
Adjusted R
Square
Std. Error of
the Estimate
1 .346a .120 -.006 .150885
a. Predictors: (Constant), WeightedMiles, WINETAX,
BEERTAX, LIQTAX
Table 2B
Table 2C
Table 3A
Model Summary

10. 9
Model R R Square
Adjusted R
Square
Std. Error of
the Estimate
1 .303a .092 -.043 .055032
a. Predictors: (Constant), WeightedMiles, BEERTAX,
LIQTAX, WINETAX
Table 3B
ANOVAa
Model
Sum of
Squares df
Mean
Square F Sig.
1 Regression .008 4 .002 .681 .611b
Residual .082 27 .003
Total .090 31
a. Dependent Variable: PERCTFATAL
b. Predictors: (Constant), WeightedMiles, BEERTAX, LIQTAX, WINETAX
Table 3C
Table 4A
Model Summary
Model R R Square
Adjusted R
Square
Std. Error of
the Estimate
1 .349a .122 -.004 .044459
a. Predictors: (Constant), WeightedMiles, WINETAX,
BEERTAX, LIQTAX

11. 10
Table 4B
ANOVAa
Model
Sum of
Squares df
Mean
Square F Sig.
1 Regression .008 4 .002 .972 .439b
Residual .055 28 .002
Total .063 32
a. Dependent Variable: BINGE
b. Predictors: (Constant), WeightedMiles, WINETAX, BEERTAX, LIQTAX
Table 4C
Table 5A
Model Summary
Model R R Square
Adjusted R
Square
Std. Error of
the Estimate
1 .385a .148 .026 .078908
a. Predictors: (Constant), WeightedMiles, WINETAX,
BEERTAX, LIQTAX
Table 5B

12. 11
ANOVAa
Model
Sum of
Squares df
Mean
Square F Sig.
1 Regression .030 4 .008 1.215 .327b
Residual .174 28 .006
Total .205 32
a. Dependent Variable: ANYDRK
b. Predictors: (Constant), WeightedMiles, WINETAX, BEERTAX, LIQTAX
Table 5C
Discussion
Was the hypothesis supported by the results?
HO: A higher alcohol tax leads to less drunk driving fatalities among youth.
The regression shown in Table 1C shows a level of significance of .054 stating that with
the data used in this experiment, we are unable to reject the null hypothesis. The number needed
to reject the null is .05, meaning that underage automobile accidents are not significantly reduced
by a higher beer tax.
While the effect of a beer tax almost reaches statistical significance, a wine or liquor tax
doesn’t even come close. This is probably because beer is the most popular and easily accessible
beverage among youth.

13. 12
Why might the results have turned out that way?
As mentioned earlier, the consumption data was “State-Specific Weighted Prevalence
Estimates of Alcohol Use and Binge Drinking Among Women 18–44 Years of Age.” (State-
Specific Alcohol Consumption Rates for 2013) This excludes any data regarding the
consumption of alcohol among men. “Higher volumes of high alcohol content beer, wine and
distilled spirits were purchased in the licensed hotels during late trading hours. Extended hours
were also associated with young crowds, more likely to be women, and lower blood alcohol
levels among women but not men” (Popova, Giesbrecht, Bekmuradov, Javadeep, 2009, p. 513).
This gives me the reason to believe that when the data that includes male consumption is
introduced, the null hypothesis will be able to be rejected.
How could the study be improved?
One way the study could be improved would be to add the consumption data among
males. Other data that could be included would be the percentage of each ethnicity represented
by state to see how drinking behaviors change between different groups. The religious affiliation
of individuals by state and the average distance driven to obtain the alcohol could also provide
valuable data for this study.
Another way the study could be improved, would be to include other types of alcohol
taxes than the current ones given. There are other alcohol taxes and they vary by state, county,
and city. Including these in the study and finding a way to properly measure the other tax options
available may have an impact.

14. 13

15. 14
References
Baughman, R., Conlin, S., Conlin, M., Pepper, J., (2000). Slippery when wet: The effects of local
alcohol access laws on highway safety. Center for Policy Research, 1-28.
Brown, R., Jewell, R., Richer, J., (1996) Endogenous alcohol prohibition and drunk driving.
Southern Economic Association, 62(4), 1043-1053.
Chaloupka, F., Grossman, M., & Saffer, H. (2002, August 1). The Effects of Price on Alcohol
Consumption and Alcohol-Related Problems. Retrieved October 6, 2015, from
http://pubs.niaaa.nih.gov/publications/arh26-1/22-34.htm
Courtney, K. E., & Polich, J. (2009). Binge drinking in young adults: Data, definitions, and
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Hanssens, D., Ornstein., (1985). Alcohol control laws and the consumption of distilled spirits
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Levine, H., & Reinarman, C. (1991). From prohibition to regulation: Lessons from alcohol
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Popova, S., Giesbrecht, N., Bekmuradov, D., Patra, Jayadeep., (2009) “EPIDEMIOLOGY AND
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social logic of problem-definition transformations since Repeal.” University of
Massachusetts Press. 61-87

16. 15
Stockwell, Tim., (2004). Addiction “Lies, Damned Lies And No Statistics: A study of
Dysfunctional Democracy in Action” Vol. 99, Issue 9, 1090-1091.
DATA:
Alcohol Rates 2000-2010, 2013-2015. (2015, February 16). Retrieved October 7, 2015, from
http://www.taxpolicycenter.org/taxfacts/displayafact.cfm?Docid=349
States & Local Areas. (2010). Retrieved October 7, 2015. www.census.gov/compendia/databooks
State-Specific Alcohol Consumption Rates for 2013. (2015, September 24). Retrieved October 7,
2015. http://www.cdc.gov/ncbddd/fasd/monitor_table.html
Quick Facts. (2010). Retrieved October 7, 2015
http://quickfacts.census.gov/qfd/states/11000.html
Responsibility.org - Fighting Drunk Driving & Underage Drinking: Foundation for Advancing
Alcohol Responsibility. (2015). Retrieved October 7, 2015.