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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.
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.
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.