Jump to ContentJump to Main Navigation
Show Summary Details
More options …

The B.E. Journal of Economic Analysis & Policy

Editor-in-Chief: Jürges, Hendrik / Ludwig, Sandra

Ed. by Auriol , Emmanuelle / Brunner, Johann / Fleck, Robert / Mendola, Mariapia / Requate, Till / Schirle, Tammy / de Vries, Frans / Zulehner, Christine

4 Issues per year


IMPACT FACTOR 2016: 0.252
5-year IMPACT FACTOR: 0.755

CiteScore 2016: 0.48

SCImago Journal Rank (SJR) 2016: 0.330
Source Normalized Impact per Paper (SNIP) 2016: 0.526

Online
ISSN
1935-1682
See all formats and pricing
More options …
Volume 13, Issue 2 (Aug 2013)

Issues

Volume 6 (2006)

Volume 4 (2004)

Volume 2 (2002)

Volume 1 (2001)

The Multitude of Alehouses: The Effects of Alcohol Outlet Density on Highway Safety

Meng-Chi Tang
  • Corresponding author
  • Department of Economics, National Chung Cheng University, 168 University Road, Min-Hsiung, Chiayi, 62102, Taiwan
  • Email:
Published Online: 2013-08-29 | DOI: https://doi.org/10.1515/bejeap-2012-0051

Abstract

This article reports the use of detailed panel data on alcoholic beverage outlet licensing in Texas to determine the effects of alcohol outlet density on highway safety. After controlling for county heterogeneity, county and year fixed effects, and county-specific time trends, this study shows that alcohol outlet density decreases expected alcohol-related traffic accidents and arrests for driving under the influence (DUI). The negative correlation can be explained according to the reduced travel distance between alcohol outlets and home, but this distance effect does not appear when the number of off-premise alcohol outlets increases. The empirical results of this study show that the off-premise alcohol outlet density is negatively related to the number of expected accidents and DUI arrests. These results indicate that on-premise consumption decreases according to the number of available off-premise outlets. The results also indicate that this effect originates mainly from the off-premise outlets that sell alcoholic products with a relatively low alcohol content.

Keywords: alcohol licenses; alcohol outlet density; driving under the influence; traffic accidents

JEL Classifications: I18; K42

References

  • Adams, S., and C. Cotti. 2008. “Drunk Driving After the Passage of Smoking Bans in Bars.” Journal of Public Economics 92(5–6):1288–305.Web of ScienceCrossrefGoogle Scholar

  • Alam, H.. 2006. “Statistics Show Alcohol-Related Deaths Don’t Play Favorites with Wet/Dry Issue.” The Lufkin Daily News, October 29.Google Scholar

  • Babor, T., R. Caetano, S. Casswell, G. Edwards, N. Giesbrecht, K. Graham, J. Grube, P. Grunewald, L. Hill, H. Holder, et al. 2003. Alcohol: No Ordinary Commodity: Research and Public Policy. New York: Oxford University Press.Google Scholar

  • Baughman, R., M. Conlin, S. Dickert-Conlin, and J. Pepper. 2001. “Slippery When Wet: The Effects of Local Alcohol Access Laws on Highway Safety.” Journal of Health Economics 20:1089–96.CrossrefGoogle Scholar

  • Brown, R. W., and R. T. Jewell. 1995. “Alcohol Availability and Alcohol-Related Motor Vehicle Accidents.” Applied Economics 27(8):759–65.Google Scholar

  • Brown, R. W., R. T. Jewell, and J. Richer. 1996. “Endogenous Alcohol Prohibition and Drunk Driving.” Southern Economic Journal 62(4):1043–54.CrossrefGoogle Scholar

  • Campbell, C. A., R. A. Hahn, R. Elder, R. Brewer, S. Chattopadhyay, J. Fielding, T. S. Naimi, T. Toomey, B. Lawrence, and J. C. Middleton. 2009. “The Effectiveness of Limiting Alcohol Outlet Density as a Means of Reducing Excessive Alcohol Consumption and Alcohol-Related Harms.” American Journal of Preventive Medicine 37(6):556–69.Web of ScienceCrossrefGoogle Scholar

  • Carpenter, C.. 2004. “How Do Zero Tolerance Drunk Driving Laws Work?” Journal of Health Economics 23:61–83.CrossrefPubMedGoogle Scholar

  • Carpenter, C., and C. Dobkin. 2010. “Alcohol Regulation and Crime.” NBER Working Papers, 2010, No. 15828.Google Scholar

  • Celines, F. X.. 2000. “Woman Forces Area to Vote on Wet-Dry Issue.” The New York Times, July 20.Google Scholar

  • Chin, H. C., and M. A. Quddus. 2003. “Applying the Random Effect Negative Binomial Model to Examine Traffic Accident Occurrence at Signalized Intersections.” Accidents Analysis and Prevention 35:253–59.Google Scholar

  • Colon, I., H. S. G. Cutter, and W. C. Jones. 1982. “Prediction of Alcoholism from Alcohol Availability, Alcohol Consumption and Demographic Data.” Journal of Studies on Alcohol 43(11):1199–213.Google Scholar

  • Conlin, M., and S. Coate. 2004. “A Group Rule: Utilitarian Approach to Voter Turnout: Theory and Evidence.” The American Economic Review 94(5):1476–504.Google Scholar

  • Cook, P. J.. 2007. Paying the Tab: The Costs and Benefits of Alcohol Control. New Jersey: Princeton University Press.Google Scholar

  • Giacopassi, D., and R. G. Winn. 1993. “Effects of County-Level Alcohol Prohibition on Motor Vehicle Accidents.” Social Science Quarterly 74(4):783–92.Google Scholar

  • Gruenewald, P. J., W. R. Ponicki, and H. D. Holder. 1993. “The Relationship of Outlet Densities to Alcohol Consumption: A Time Series Cross-Sectional Analysis.” Alcoholism: Clinical and Experimental Research 17(1):38–47.CrossrefGoogle Scholar

  • Heather, N., and T. Stockwell. 2004. The Essential Handbook of Treatment and Prevention of Alcohol Problems. England: John Wiley & Sons.Google Scholar

  • Jackson, C. K., and E. M. Owens. 2011. “One for the Road: Public Transportation, Alcohol Consumption, and Intoxicated Driving.” Journal of Public Economics 95(1–2):106–21.Web of ScienceGoogle Scholar

  • Sloan, F. A., E. M. Stout, K. Whetten-Goldstein, and L. Liang. 2000. Drinkers, Drivers, and Bartenders: Balancing Private Choices and Public Accountability. Chicago: University of Chicago Press.Google Scholar

  • Livingston, M., T. Chikritzhs, and R. Room. 2007. “Changing the Density of Alcohol Outlets to Reduce Alcohol-Related Problems.” Drug and Alcohol Review 26(5):557–66.CrossrefGoogle Scholar

  • McCarthy, P.. 1999. “Public Policy and Highway Safety: A City-Wide Perspective.” Regional Science and Urban Economics 29(2):231–44.CrossrefGoogle Scholar

  • McCarthy, P.. 2003. “Alcohol-Related Crashes and Alcohol Availability in Grass-Roots Communities.” Applied Economics 35(11):1331–38.CrossrefGoogle Scholar

  • Smith, A.. 1976. An Inquiry into the Nature and Causes of the Wealth of Nations. Oxford: Clarendon Press.Google Scholar

  • Snow, R. W., and J. W. Landrum. 1986. “Drinking Locations and Frequency of Drunkenness among Mississippi DUI Offenders.” American Journal of Drug Alcohol Abuse 12(4):389–402.CrossrefGoogle Scholar

  • Watts, R. K., and J. Rabow. 1983. “Alcohol Availability and Alcohol-Related Problems in 213 California Cities.” Alcoholism: Clinical and Experimental Research 7(1):47–58.CrossrefGoogle Scholar

About the article

Published Online: 2013-08-29


Adams and Cotti (2008) indicated that additional miles driven by alcohol consumers traveling to a remote bar may offset the reduction in driving from drinkers choosing not to drink when a local alcohol outlet is not available.

For example, see The New York Times, 20 July 2000 (Celines 2000) and The Lufkin Daily News, 29 October 2006 (Alam 2006).

Many studies have examined the effects of alcohol availability on alcohol-related problems, presenting mixed results. For example, see the surveys by Babor et al. (2003, chapter 7); Heather and Stockwell (2004, chapter 13); Cook (2007, chapter 10); Livingston, Chikritzhs, and Room (2007); and Carpenter and Dobkin (2010).

Although some studies have shown positive relationships between alcohol outlet density and highway safety (Giacopassi and Winn 1993; Brown and Jewell 1995; Brown, Jewell, and Richer 1996; and McCarthy 1999), other studies show negative relationships (Colon, Cutter, and Jones 1982; Liang et al. 2000; Baughman et al. 2001; and McCarthy 2003).

Carpenter and Dobkin (2010) argued that the omitted variable bias problem had not been appropriately addressed in the literature. Heather and Stockwell (2004) also argued that evidence for the association between alcohol outlet density, drinking, and alcohol-related problems comes mainly from cross-sectional and longitudinal studies, and only a few studies have managed to conduct panel data analysis of the trends across both time and place.

A few researchers, including Watts and Rabow (1983), Snow and Landrum (1986), and Jackson and Owens (2011), have examined this type of alcohol-related offense.

This study is based on an expanded dataset from Baughman et al. (2001), which was collected from sources such as the Texas Department of Public Safety, Texas Transportation and Planning Division, Texas Vehicle Titles and Registration Division, and U.S. Department of Congress.

Baughman et al. (2001) provided additional details regarding changes in county liquor laws during our sample period.

For example, many off-premise liquor stores possess both beer/wine and liquor licenses. In this study, such outlets are considered to be both beer/wine and liquor outlets. If an alcohol outlet was permitted to sell beer for off-premise consumption and liquor for on-premise consumption, that outlet was considered to be both an on- and off-premise outlets.

The Expand group contains 2,044 county/year observations; the Same group contains 1,760 observations; and the Zero group contains 1,784 observations during the sample period.

The control variables include whether a county is wet, police expenditures, population, per capita income, total vehicle miles driven, total vehicle miles driven on the highway, number of registered vehicles, and religious affiliations.

For example, by holding the alcohol price as fixed, the greater numbers of off-premise alcohol outlets in close proximity reduces the convenience costs required of alcohol purchase, thus increasing off-premise alcohol consumption accordingly. Without separating the effects of different types of alcohol outlets, Gruenewald, Ponicki, and Holder (1993) found that alcohol availability is positively related to alcohol sales. Campbell et al. (2009) conducted a comprehensive survey of the relationship between on- and off-premise stores and alcohol consumption. In addition, a more competitive environment from a greater density of alcohol outlets may also reduce the price of alcohol, which in turn increases consumption. I thank an anonymous referee for highlighting this point.

A similar analysis of the effect of liquor content on highway safety can also be performed by decomposing N into outlets that sell beer/wine and outlets that sell liquor.

Some strong short-term police enforcement responses to policy change are likely, yet these might not be captured by police expenditures. Compared to counties without policy changes to counties with changes, counties with changes had more increases in DUI on average (3.76), whereas counties without changes had an average decreasing trend (–1.66). Conversely, the changes in alcohol-related accidents in these counties with policy changes were negative after the policy implementation (–0.97) compared to the positive trend for counties without changes (0.54). Therefore, policy dummies are applied in the regressions to control this potential effect.

The percentages of Catholic and Baptist residents were included in the analysis, because those percentages affected the results of the Texas liquor referendum during the sample period. See Conlin and Coate (2004) for empirical evidence of this relationship.

Carpenter (2004) suggested that a linear time trend controls for some time-varying variables that might determine alcohol-related behaviors. For example, a less stringent social attitude toward drinking within a county may lead to more new outlets in the county, but also more alcohol-related problems. Baughman et al. (2001) applied a similar strategy to estimate the effects of alcohol access laws on highway safety. They found that the estimated effects were significantly different before and after the county-specific trend had been controlled.

When the lagged variables were included in the regression, the first observation of each county was subtracted from the sample, and the observations became 5,334 for the accident regressions. The arrest regressions were not affected.

The results controlling two periods of lagged outlet density are similar to those for controlling only one period; therefore, they are not reported.

A potential explanation for this result is that the off-premise outlets provide cheaper alcoholic products than the on-premise outlets do.

For example, Column (1) in Table 4 shows that one more beer/wine outlet per hundred square miles reduces the average number of accidents by 14%. Column (4) shows that one more beer/wine outlet per hundred square miles reduces the average number of DUI arrests by ~11%.

Specifically, Column (3) shows that one more off-premise outlet per hundred square miles that sells beer/wine reduces the number of accidents by 20% from the average number of accidents.

Regression including the square of liquor outlet density shows that the positive effect of liquor outlet on accidents decreases as the liquor outlet availability increases. I thank an anonymous referee for highlighting this point.

However, Jackson and Owens (2011) did not differentiate between public intoxication arrests and other arrests, including those for open-container violations.

Chin and Quddus (2003) applied the same econometric model to examine the elements affecting intersection safety.

Similar estimates were also obtained from a fixed-effects negative binomial regressions and are not reported here. A Hausman test did not reject the null hypothesis that the estimated effects of both on- and off-premise outlet densities on alcohol-related crimes are different between random-effects and fixed-effects estimators. The author thanks an anonymous referee for indicating this.

Marginal effects are not reported here, but are available on request.

Table 6 also shows that, contrary to the effects of local on-premise outlets, on-premise outlets in adjacent counties have positive effects on local highway safety. The distant effect provides a probable explanation, because the required travel distance to outlets in adjacent counties is greater than that of local outlets. Because the off-premise outlets in both local and adjacent counties have only the availability effect, Table 6 indicates that their effects on local highway safety are similar and differ only in level. Table 6 shows that both the availability effect and the distance effect are important channels through which alcohol outlets affect local highway safety.


Citation Information: The B.E. Journal of Economic Analysis & Policy, ISSN (Online) 1935-1682, ISSN (Print) 2194-6108, DOI: https://doi.org/10.1515/bejeap-2012-0051.

Export Citation

©2013 by Walter de Gruyter Berlin / Boston. Copyright Clearance Center

Comments (0)

Please log in or register to comment.
Log in