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Availability restrictions and alcohol consumption: A case of restricted hours of alcohol sales in Russian regions

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Kolosnitsyna, M., Sitdikov, M., & Khorkina, N. (2014). Availability restrictions and alcohol consumption: A case of restricted hours of alcohol sales in Russian regions. The International Journal Of Alcohol And Drug Research, 3 (3), 193 – 201. doi: http://dx.doi.org/10.7895/ijadr.v3i3.154 Aim: To determine how new restrictions on hours of alcohol retail sales influence alcohol consumption in Russia. Design: Natural experiment with combined regional and micro-data. Setting/Participants: Cross-sectional samples from the Russian Longitudinal Monitoring Survey, corresponding to waves 18 and 19, years 2009–2010, 32 Russian regions and more than 7,000 adults (aged 15 and up) consuming alcohol at least once per month. Measures: Descriptive analysis of per capita alcohol sales at the regional level and regression analysis of pure spirit consumption at the individual level, controlling for various socioeconomic factors, including sales bans. Findings: We revealed a significant positive correlation between the amount of alcohol consumed and the number of hours of allowed alcohol sales when other factors were controlled. The results gained from analyzing the micro-data were confirmed using the regional sales information. In terms of drinking reduction, sales restrictions in the evening hours seem more efficient than restrictions in the morning hours. Restricted hours of sale do not increase consumption of beer or home-distilled alcohol. Conclusions: Alcohol consumption depends on the hours of sale, all else being equal. Restricting the legal hours of alcohol sales in Russian regions has the potential to reduce consumption levels. These findings indicate a need for a further reduction in sales hours in the regions where heavy drinking is especially widespread.
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doi: 10.7895/ijadr.v3i3.154 IJADR, 2014, 3(3), 193 – 201 ISSN: 1925-7066
Availability restrictions and alcohol consumption: A case of
restricted hours of alcohol sales in Russian regions
Marina Kolosnitsyna, Marat Sitdikov, and Natalia Khorkina
Department of Applied Economics, Higher School of Economics, Moscow
Abstract
Aim: To determine how new restrictions on hours of alcohol retail sales influence alcohol consumption in Russia.
Design: Natural experiment with combined regional and micro-data.
Setting/Participants: Cross-sectional samples from the Russian Longitudinal Monitoring Survey, corresponding to waves 18
and 19, years 20092010, 32 Russian regions and more than 7,000 adults (aged 15 and up) consuming alcohol at least once per
month.
Measures: Descriptive analysis of per capita alcohol sales at the regional level and regression analysis of pure spirit
consumption at the individual level, controlling for various socioeconomic factors, including sales bans.
Findings: We revealed a significant positive correlation between the amount of alcohol consumed and the number of hours of
allowed alcohol sales when other factors were controlled. The results gained from analyzing the micro-data were confirmed
using the regional sales information. In terms of drinking reduction, sales restrictions in the evening hours seem more efficient
than restrictions in the morning hours. Restricted hours of sale do not increase consumption of beer or home-distilled alcohol.
Conclusions: Alcohol consumption depends on the hours of sale, all else being equal. Restricting the legal hours of alcohol sales
in Russian regions has the potential to reduce consumption levels. These findings indicate a need for a further reduction in sales
hours in the regions where heavy drinking is especially widespread.
Excessive alcohol consumption has long been typical of
unhealthy behavior in many countries in the world. The
consequences associated with drinking include illness and
reduced life expectancy for the consumer and negative
external effects for society, such as domestic violence,
crime, traffic and workplace accidents (Babor et al., 2010;
World Health Organization [WHO], 2011). From the
perspective of economic theory, these are all arguments for
governmental intervention in the process of individual
consumer choice.
The idea of restricting the sale of alcohol is based on a fact
well known among economists: the “supply side” of any
market influences its “demand side.” A review by Hahn et
al. (2010) provided an assessment of the effects of
increasing sales hours in several high-income countries.
The researchers showed that extending the sales period by
two or more hours increased harmful alcohol consumption
(pр. 594-–598). Based on 14 studies, Middleton et al.
(2010) analyzed the results of changes to limits on the days
on which alcoholic beverages were sold. They found that
removing limits on sales increased alcohol consumption
(pр. 583584). Especially interesting was a natural
experiment in Sweden, where, in the year 2000, legislation
was changed, allowing alcohol retail shops that had
previously been closed on Saturdays to open in several
counties. In other counties, the rules remained the same.
Nordström and Skog (2003) used these data to estimate the
impact of an additional day of alcohol sales. The
researchers found a statistically significant increase in
alcohol consumption in those counties where Saturday
sales occurred (p. 397). A detailed review of research
papers devoted to restrictions on hours and days of alcohol
sales can be found in a paper by Popova, Giesbrecht,
Bekmuradov, and Patra (2009). The authors analyzed 15
articles based on data from different countries and found a
positive correlation between the hours and days of sales
and alcohol consumption. Another review of temporal
restriction practices and relevant scientific evidence was
provided in the comprehensive volume “Alcohol: No
Ordinary Commodity” (Babor et al., 2010). The authors
concluded that the level of effectiveness of restrictions on
times of sale is relatively high, and that research solidly
supports these measures. The WHO Global Strategy to
IJADR
International Journal of Alcohol and Drug Research
The Official Journal of the Kettil Bruun Society for Social and Epidemiological Research on Alcohol
Correspondence: Marina Kolosnitsyna, Department of Applied Economics, Higher School of Economics, #4212, 26, Shabolovka st., Moscow 119049 Russia.
Telephone: +7 495 628 99 62; E-mail: mkolosnitsyna@hse.ru
Financial support: Basic Research Program at the National Research University Higher School of Economics (HSE).
Acknowledgements: The authors thank Dr. Sornpaisarn, Editor for the Special Issue of IJADR, and two anonymous reviewers for their valuable comments.
Keywords: alcohol, alcohol policy, temporal bans, restricted hours of sale, Russia
194 Marina Kolosnitsyna et al.
Reduce the Harmful Use of Alcohol (WHO, 2010) listed
the “availability of alcohol” among recommended target
areas for national action.
Russia has consistently been among those countries with
the highest levels of alcohol intake, and it has the most
dangerous model of consumption, according to the WHO
(2011). Alcohol policy in Russia has a long and complex
history. A total prohibition of alcohol sales and
consumption was established by Tzar Nicolas II’s decree in
1914 during World War I, and provided immediate positive
results: per capita alcohol consumption decreased from 4.7
liters of pure spirits in 1913 to 0.2 liters in 1915
(Gosudarstvennaya Duma Rossiyskoy Federatzii, 1994).
After the revolution in 1917, the new Bolshevik
government maintained the prohibition until 1923, when it
was abolished because of a high prevalence of home
brewing and a need for financial resources for new
governmental campaigns. Later in the USSR’s history,
there were numerous episodes of restrictions being set and
then abolished or left unenforced.
In 1985, Gorbachev began a large-scale anti-alcohol
campaign that limited alcohol sales to the hours from 2
p.m. until 7 p.m. (Soviet Ministrov SSSR, 1985). These
restrictions were in place until 1990. During this
campaign, per capita alcohol sales were reduced by 60%
(Khalturina & Korotaev, 2008, р. 27).
Unfortunately, after the collapse of the USSR, the emerging
Russian government had higher priorities than maintaining
the anti-alcohol campaign. As part of rapidly changing
market relationships, the state lost its monopoly on alcohol
production and sales and its control over restricted hours of
sale. Many new producers, including large multinationals,
entered the alcohol market. According to the Federal State
Statistical Service (Rosstat), alcohol sales in liters of pure
spirit per adult increased from 7.1 in 1990 to 11.6 in 2007
and then declined slightly, to 10.7, in 2010 (Rosstat, 2012a,
p. 81, p. 535). Research on the Russian alcohol situation
after 1991 often stresses the negative role of any state
alcohol policy. For example, Treisman (2010) argued that
the increasing death rates observed in Russia in early 1990
were caused by alcohol pricing policy (the low relative
price of vodka) rather than by the distress of political and
economic transition. Bhattacharya, Gathmann, and Miller
(2012) described the end of the Gorbachev anti-alcohol
campaign as the main factor contributing to the so-called
Russian mortality crisis.
Recently, the Russian government has turned to more
radical anti-alcohol policy instruments. The key document
outlining this approach, “Concept for State Policy to
Reduce the Scale of Alcohol Abuse and Prevent
Alcoholism among the Population of the Russian
Federation,” was approved in 2009 (Pravitel’stvo
Rossijskoi Federatzii, 2009). All Russian regions obtained
the right (but not the obligation) to establish restrictions on
hours of alcohol sales. In 2009, few regions had such
restrictions in place. In contrast, by 2010, 72 out of 83
regions had adopted a ban on all alcoholic beverages,
except beer, during various night hours (see Appendix A).
Since July 2011, off-premises sales of alcohol have been
forbidden from 11 p.m. until 8 a.m. across the country;
regional authorities now have the authority only to tighten
this measure, if they wish. Hence, we no longer observe
significant regional variations in restricted hours of sale.
However, the unique situation that existed during the year
2010 created a natural experiment that makes it possible to
evaluate the efficiency of the newly adopted restrictions.
Several potential consequences of such restrictions merit
investigation: First, it is important to understand how the
existence and severity of temporal bans correlate with the
amount of alcohol consumed. Second, it is unclear whether
morning and evening restrictions are equally effective.
Lastly, it is not clear how the ban on retail alcohol sales
corresponds with the consumption of home-distilled
beverages and beer, which are not subject to restrictions.
Hence, the following four hypotheses were tested:
H1: A temporal ban on alcohol sales reduces
individual alcohol consumption, all else being equal.
H2: Evening restrictions are more efficient than
morning restrictions (as a greater amount of alcohol is
normally sold in the evening hours).
H3: Availability restrictions on strong alcohol do not
necessarily induce the consumption of beer as a
substitute.
H4: Availability restrictions on retail alcohol sales do
not necessarily induce the consumption of home-
distilled alcohol as a substitute.
Data and Methods
To estimate the impact of the restricted hours of sale in
2010, we used regional and micro-level data. First, we
have official statistical information on alcohol sales by type
of beverage (vodka, cognac, wine, beer) provided by the
Rosstat for all Russian regions (Rosstat, 2011, pp. 722
723). We used these data to estimate per capita sales of
vodka, cognac and wines in liters of pure spirits in every
Russian region. Beer was not subject to restrictions
because, until 2013, it was not considered to be alcoholic.
Thus, we calculated per capita sales of beer separately.
Two regions with sales levels close to zero (Chechen
Republic and Republic of Ingushetia) were excluded from
observation, as were three autonomous districts without
separate data on alcohol sales, and the Kurgan region,
where sales restrictions were only partial. Thus, of 83
Russian regions, we analyzed 77, of which 68 had various
temporal bans in 2010, and nine did not (see Appendix A).
The regions were grouped by the number of hours when
alcohol sales were permitted, ranging from those which
permitted sales for eight hours of the day, to those which
allowed 10 or 12 hours of sales, to those with no
restrictions at all. We then compared the average per-adult
sales dynamics (20092010) for alcoholic beverages that
were subject to restrictions and for beer in these seven
regional groups. These calculations were repeated for five
regional groups with different closure hours.
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Availability restrictions and alcohol consumption 195
Another type of micro-data was provided by the Russian
Longitudinal Monitoring Survey (RLMS-HSE), conducted
by the Higher School of Economics and ZAO
“Demoscope” together with the Carolina Population
Center, University of North Carolina at Chapel Hill, and
the Institute of Sociology RAS (National Research
University Higher School of Economics [HSE], 2011). The
RLMS-HSE is a household-based, nationally representative
survey, and its individual questionnaires collect
information on respondents’ well-being, including the
amounts of alcohol consumed monthly by type of beverage.
We used a cross-sectional sample from round 19 of the
RLMS-HSE (year 2010). Of 32 regions included in the
survey in 2010, 28 had introduced restrictions on hours of
alcohol sales; the other four had no restrictions.
The subsample of individuals consuming alcoholic
beverages at least once per month amounted to 7,286
adults. Among these adults, the largest share3,128
(42.9%)reported drinking only vodka and wine, which
were banned from sale at night. In total, 1,561 (21.4%)
consumed only beer. The number of those individuals
drinking only vodka, wine and beer (but not home-distilled
wine, or samogon) amounted to 2,221 persons (30.5%).
Samogon consumers were less numerous, accounting for
376 persons, or 5.2% of those individuals drinking alcohol.
Thus, the main patterns of alcohol drinking in Russia were
1) vodka and wine, 2) vodka and wine paired with beer,
and 3) only beer (Figure 1).
We constructed a multiple linear regression model, with the
logarithm of the total amount of individual consumption of
alcohol in grams of pure spirits per month as the dependent
variable. To estimate this variable, we summarized the
amounts of all alcoholic beverages consumed by every
individual (adjusted according to alcohol concentration). In
line with previous research on alcohol consumption
(Andrienko & Nemtsov, 2006; Cerdá, Johnson-Lawrence,
& Galea, 2011; Contoyannis & Jones, 2004; Cutler &
Lleras-Muney, 2010; Gottlieb & Baker, 1986; Le, Ahern, &
Galea, 2010; Leonard & Mudar, 2003; Livingstone &
Room, 2008; Neufeld, Peters, Rani, Bonu, & Brooner,
2004; Park & Kang, 2008; Zhou et al., 2006), we used
numerous socioeconomic factors as independent variables
(including gender, family status, the type of settlement,
educational level, average household income, and others).
Sales restrictions were modeled in three different ways: as
the total number of hours when alcohol sales were allowed,
as the time of sales closure and as the time of sales start.
These variables were used as exogenous variables, and
their influence on total consumption was estimated.
We then estimated the same model for the amount of
individual consumption of alcohol, excluding beer and
samogon, which were not subject to nighttime sales
restrictions. This modeling allowed us to track the impact
of bans on the consumption of the beverages that were
subject to restrictions.
Figure 1
Main patterns of alcohol consumption in Russia, 2010 (share of those individuals drinking certain beverages among all
alcohol consumers, %)
Note. The data in this figure are from the HSE (2011). Russian Longitudinal Monitoring Survey - Higher School of Economics. Available at:
http://www.hse.ru/org/hse/rlms
Vodka and wine
only (42.9%)
Vodka, wine
and beer only
(30.5%)
Beer only
(21.4%)
–––––– IJADR 3(3) ––––––
196 Marina Kolosnitsyna et al.
As mentioned above, beer was not subject to restricted
hours of sale in 2010. Thus, theoretically, beer could have
been consumed as a replacement for other alcoholic
beverages. Several research papers on alcohol
consumption in Russia have already shown that beer is a
supplement to strong drinks. For example, Kossova,
Kossova, and Sukhodoev (2012) estimated a regression
model of beer consumption based on regional sales data
and found “a positive logarithmic relationship between beer
and vodka” (p. 14). In Russia, where more than half of all
alcohol consumed is vodka, the rapidly growing
consumption of beer is not accompanied by a comparable
decline in the consumption of strong drinks (United
Nations Development Program [UNDP], 2011, pp. 8990).
To assess the possible substitution effect caused by sales
bans, we estimated a separate regression model for beer
that included variables for temporal restrictions.
A common criticism of availability restriction measures is
that they may induce increased consumption of home-
distilled substitutes. In fact, descriptive data from the
RLMS-HSE and other surveys show that samogon is not
currently popular, as its share of consumers has decreased
consistently (UNDP, 2011, pp. 89–90). However, we
estimated the share of the population drinking samogon and
the average intake of individuals who drink this beverage
separately for two groups of regions (with and without
restrictions). The same regression model was estimated for
samogon consumption as for the total amount of alcohol
consumption and included the exogenous variables
reflecting regional sales bans.
Results
An analysis of descriptive statistics shows that in regions
where alcoholic beverages could be sold for 17 or more
hours per day, the average level of sales per person
increased between 2009 and 2010. In contrast, in regions
with relatively stringent restrictions, sales per person
dropped (see Table 1). In the case of beer, which could be
bought all day, there was not such a clear relationship
between consumption rates and number of hours. Only
Chukotkaa region with a reputation for high rates of
alcoholismdemonstrated a rapid growth of per capita
sales of beer; the other regions showed a slight decrease or
slight growth.
In those regions where liquor could be sold until 8, 9, 10 or
11 p.m., per capita sales of alcoholic beverages (excluding
beer) declined in 2010 from 2009. Conversely, in the
territories where alcohol sales stopped at midnight or later,
or did not stop, we observed increasing per capita sales (see
Table 2).
RLMS-HSE data on individuals grouped by region reveal
that the share of the adult population drinking home-
distilled alcohol (samogon) declined in all regions,
regardless of policies controlling retail alcohol sales.
However, the average daily intake of those individuals who
prefer samogon increased in the regions without sales
restrictions. In contrast, in the group of territories where
restrictions were set, the amount of samogon consumed per
person declined (Table 3).
Table 1
Sales of alcoholic beverages per adult, in liters of pure spirit, by groups of regions with various hours of sale, 20092010
Number of hours
per day when
alcohol sales
permitted
Number
of
regions
Alcohol sales per adult, in
liters of pure spirit
(excluding beer)
Growth
rate,
%
Beer sales per adult, in
liters of pure spirit
Growth
rate,
%
2010 2009 2010 2009
8 1 8.03 8.09 -0.74% 0.89 0.52 71.15%
1012 15 5.94 6.24 -4.70% 2.89 2.91 -0.01%
1314 13 5.53 5.66 -2.34% 2.89 2.88 0.00%
15 15 6.17 6.20 -0.41% 3.48 3.43 1.46%
16 17 6.85 6.88 -0.53% 3.35 3.50 -4.29%
1719 7 5.15 5.13 0.56% 2.85 2.80 1.79%
24 9 5.78 5.59 3.38% 3.46 3.40 1.76%
Note. The data in this table are from the Rosstat (2010). Regiony Rossii. Sozialno-ekonomicheskiye pokazateli. Available at:
http://www.gks.ru/wps/wcm/connect/rosstat_main/rosstat/ru/statistics/publications/catalog/doc_1138623506156 [Rosstat (2010). Regions of
Russia. Socio-economic indicators.]; Rosstat (2011). Regiony Rossii. Sozialno-ekonomicheskiye pokazateli. Available at:
http://www.gks.ru/wps/wcm/connect/rosstat_main/rosstat/ru/statistics/publications/catalog/doc_1138623506156 [Rosstat (2011). Regions of
Russia. Socio-economic indicators.]
–––––– IJADR 3(3) ––––––
Availability restrictions and alcohol consumption 197
Table 2
Sales of alcoholic beverages per adult, in liters of pure spirit, by groups of regions with various closure times, 20092010
Closing time for
alcohol sales Number
of regions
Alcohol sales per adult in
liters of pure spirit (excluding
beer) Growth rate,
%
Beer sales per adult
in liters of pure spirit Growth rate,
%
2010 2009 2010 2009
8–9 p.m. 7 6.14 6.29 -2.36% 2.68 2.73 -1.83%
10 p.m. 17 5.78 5.95 -2.76% 2.95 2.97 -0.67%
11 p.m. 37 6.16 6.28 -1.91% 3.21 3.25 -1.23%
122 a.m. 7 6.40 6.22 2.94% 3.28 3.17 3.47%
No restrictions 9 5.78 5.59 3.38% 3.46 3.40 1.76%
Note. The data in this table are from the Rosstat (2010). Regiony Rossii. Sozialno-ekonomicheskiye pokazateli. Available at:
http://www.gks.ru/wps/wcm/connect/rosstat_main/rosstat/ru/statistics/publications/catalog/doc_1138623506156 [Rosstat (2010). Regions of
Russia. Socio-economic indicators.]; Rosstat (2011). Regiony Rossii. Sozialno-ekonomicheskiye pokazateli. Available at:
http://www.gks.ru/wps/wcm/connect/rosstat_main/rosstat/ru/statistics/publications/catalog/doc_1138623506156 [Rosstat (2011). Regions of
Russia. Socio-economic indicators.]
Table 3
Samogon consumption in regions with temporal bans on alcohol sales and in regions without restrictions, 20092010
Regions with temporal bans Regions without restrictions
Percentage of adult
population drinking
samogon
Average daily amount,
in grams (for those
drinking samogon)
Percentage of adult
population drinking
samogon
Average daily amount, in
grams (for those drinking
samogon)
2009 2.66% 260.7 4.36% 270.0
2010 2.11% 235.5 3.13% 276.6
Note. The data in this table are from the HSE (2011). Russian Longitudinal Monitoring SurveyHigher School of Economics. Available at:
http://www.hse.ru/org/hse/rlms
Table 4 presents a brief summary of the regression analysis
results. All of the models were statistically significant,
with high levels of F-statistics. Most of the beta-
coefficients were statistically significant and had the
expected signs. Integrating the results of models 1 to 4, we
can state the following:
1) The number of hours during which alcohol sales are
allowed correlates positively with individual alcohol
consumption, all else being equal (models 1.1, 2.1,
3.1, 4.1).
2) A negative coefficient sign for the variable of sales
start shows that the later an outlet opens, the less a
person will drink. A positive sign before the
coefficient of the closure time variable indicates that
the longer a shop is open, the more a person will
consume. However, the magnitude of the evening ban
coefficient is 3.5 to 4 times higher than that of the
morning ban coefficient (models 1.2, 1.3, 2.2, 2.3, 3.2,
3.3).
3) Estimates of models 3.1 to 3.3 demonstrate that
individual beer consumption reacts to restricted hours
of sale in the same way as the consumption of vodka
and wine, which were subject to night sales
restrictions.
4) Estimates of models 4.1 to 4.3 reveal non-significant
β-coefficients for the variables of morning and
evening restrictions. The only significant coefficient
for the variable “Number of hours” has the same sign
as in all of the models for total alcohol and for beer.
Thus, we can argue that the individual consumption of
vodka, beer and samogon is lower in territories where
the banned period is longer, all else being equal.
The regression analysis results coincide with the regional
macro-data presented in Tables 1 to 3 and thus verify the
findings. The above hypotheses were thus confirmed.
–––––– IJADR 3(3) ––––––
198 Marina Kolosnitsyna et al.
Table 4
Influence of restricted hours of sale on individual alcohol consumption: Regression analysis results
Dependent variable:
individual monthly
consumption of
alcoholic beverages in
grams of pure spirit,
ln N Independent variables of restrictions Coefficient
estimate p-value Std.
error R2 Number of
observations
All alcoholic
beverages (including
beer and samogon)
1.1 Number of hours when alcohol sales
were permitted 0.008** 0.002 0.003 0.236 6,032
1.2 Time when sales end in the evening (9
p.m., 10 p.m., etc.) 0.076*** 0.000 0.015 0.229 5,226
1.3 Time when sales begin in the morning (6
a.m., 7 a.m., etc.) -0.025*** 0.000 0.006 0.228 5,226
All alcoholic
beverages (excluding
beer and samogon)
2.1 Number of hours when alcohol sales
were permitted 0.009*** 0.000 0.002 0.320 5,516
2.2 Time when sales end in the evening (9
p.m., 10 p.m., etc.) 0.077*** 0.000 0.014 0.316 4,858
2.3 Time when sales begin in the morning (6
a.m., 7 a.m., etc.) -0.020*** 0.000 0.005 0.313 4,858
Beer
3.1 Number of hours when alcohol sales
were permitted 0.010*** 0.000 0.002 0.174 3,895
3.2 Time when sales end in the evening (9
p.m., 10 p.m., etc.) 0.082*** 0.000 0.014 0.178 3,340
3.3 Time when sales begin in the morning (6
a.m., 7 a.m., etc.) -0.027*** 0.000 0.005 0.177 3,340
Samogon
4.1 Number of hours when alcohol sales
were permitted 0.021** 0.004 0.007 0.249 343
4.2 Time when sales end in the evening (9
p.m., 10 p.m., etc.) -0.004ns 0.941 0.059 0.214 285
4.3 Time when sales begin in the morning (6
a.m., 7 a.m., etc.) 0.009 ns 0.518 0.014 0.215 285
** p < .01; *** p < .001; ns = non-significant
Discussion
The results of this study show that the amount of individual
alcohol intake is positively correlated with the number of
hours when sales are permitted. This observation is true for
all types of alcohol consumption (total alcohol
consumption, total alcohol consumption without beer and
samogon, beer consumption, and even samogon
consumption). These results are consistent with the
findings of systematic reviews performed by Babor et al.
(2010), Hahn et al. (2010) and Popova et al. (2009). In
addition, in this study, we found that not only is alcohol
consumption influenced by the number of hours when sales
are forbidden, but that the times when alcohol sales start
and close are also important. Based on regression
coefficient magnitudes, we can argue that closure time is a
more efficient instrument to reduce drinking.
In our study, we did not observe any substitution effect
between beer and vodka at the individual level, a result that
is consistent with the findings of Kossova et al. (2012) at
the macro level. We also discovered no evidence that
restricted hours of retail alcohol sales led to greater
consumption of home-distilled alcohol. Previous research
in Russia revealed a tendency of consumers to substitute
samogon for vodka when the price of the latter increased
(Andrienko & Nemtsov, 2006). Our results concerning
restricted hours of sale do not confirm that home-distilled
alcohol is consumed as a substitute for commercially
produced beverages, and particularly vodka.
Price regulation is often named as one of the most efficient
measures for drinking reduction (Babor et al., 2010,
Treisman, 2010, WHO, 2010). In our study, we did not
estimate the influence of alcohol pricing, for two reasons.
First, in the regression analysis, we used cross-sectional
data for only one year, so we could not track price growth.
Second, and perhaps more importantly, the real price of
alcohol in Russia is still very low. In 2010, a floor price
was introduced for vodka for the first time and was set at
89 rubles for a half-liter bottle, which was equal to the price
of 3 kilos of bread or 3 liters of milk (Rosstat, 2012b, pp.
66-67). The excise tax on strong alcohol in Russia is still
several times less than in European countries, including
Finland and Poland, and this tax comprises less than 50%
of the retail price (Kalinin, Kolosnitsyna, & Zasimova,
–––––– IJADR 3(3) ––––––
Availability restrictions and alcohol consumption 199
2011, p. 21). Therefore, we do not believe that alcohol
prices had a significant effect on consumption in 2010.
However, as alcohol taxes have recently increased, we are
planning to continue this research using panel data and to
estimate the influence of price along with that of restricted
hours of sale.
Conclusions
The investigated case has confirmed that alcohol
consumption depends on the hours of sale, all else being
equal. The results are consistent with the general economic
theory that supply influences demand. It is important to
note that the Russian regions that banned nighttime liquor
sales demonstrated relatively low consumption of both
commercially available alcohol and home-distilled wine
and beer, which were not subject to restrictions. Restricted
hours of alcohol sales in Russian regions have the potential
to reduce total consumption levels. These findings indicate
a need for a further reduction in sales hours in regions
where heavy drinking is especially widespread. Evening
sales closures could be effective in confronting the Russian
culture of binge drinking.
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Appendix A
Temporal bans on the sales of alcoholic beverages in Russian regions, 2010
Regions Hours when sales
are illegal Regions Hours when sales
are illegal
1 Chechen Republic
a
10 a.m.8 a.m. 43 Tambov region
b
11 p.m.8 a.m.
2 Republic of Ingushetiaa 6 p.m.10 a.m. 44 Tomsk regionb 11 p.m.8 a.m.
3 Сhukotka autonomous district 8 p.m.12 p.m. 45 Volgograd regionb 11 p.m.8 a.m.
4 Nenets autonomous districta 8 p.m.11 a.m. 46 Vologda region 11 p.m.8 a.m.
5 Moscow region
b
9 p.m.11 a.m. 47 Yaroslavl region 11 p.m.8 a.m.
6 Murmansk region 9 p.m.11 a.m. 48 Sakhalin region 12 a.m.9 a.m.
7 Republic of North Ossetia
Alania 9 p.m.11 a.m. 49 Chelyabinsk regionb 11 p.m.7 a.m.
8 Tver regionb 9 p.m.10 a.m. 50 Chuvashi Republicb 11 p.m.7 a.m.
9 Jewish autonomous region 10 p.m.11 a.m. 51 Kirov region 11 p.m.7 a.m.
10 Kamchatka territory 10 p.m.11 a.m. 52 Leningrad region
b
11 p.m.7 a.m.
11 Krasnodar territory b 10 p.m.11 a.m. 53 Pskov region 11 p.m.7 a.m.
12 Ulyanovsk region 8 p.m.8 a.m. 54 Republic of Buryatia 11 p.m.7 a.m.
13 Ivanovo region 9 p.m.9 a.m. 55 Republic of Karelia 11 p.m.7 a.m.
14 Kabardino-Balkarian Republic
b
10 p.m.10 a.m. 56 Rostov region
b
11 p.m.7 a.m.
15 Orenburg region
b
10 p.m.10 a.m. 57 The City of Sankt-Petersburg
b
11 p.m.7 a.m.
16 Republic of Dagestan 10 p.m.10 a.m. 58 Tula regionb 11 p.m.7 a.m.
17 Republic of Tatarstanb 10 p.m.10 a.m. 59 Tyumen region 11 p.m.7 a.m.
18 The City of Moscowb 10 p.m.10 a.m. 60 Udmurtian Republicb 11 p.m.7 a.m.
19 Magadan region 11 p.m.11 a.m. 61 Vladimir region 11 p.m.7 a.m.
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Availability restrictions and alcohol consumption 201
Regions Hours when sales
are illegal Regions Hours when sales
are illegal
20 Kemerovo region 10 p.m.9 a.m. 62 Voronezh region 11 p.m.7 a.m.
21 Novosibirsk regionb 10 p.m.9 a.m. 63 Yamalo-Nenets autonomous districta 11 p.m.7 a.m.
22 Primorsky territoryb 10 p.m.9 a.m. 64 Astrakhan region 12 a.m.8 a.m.
23 Stavropol territory
b
10 p.m.9 a.m. 65 Zabaikalsk territory 12 a.m.8 a.m.
24 Republic of Tuva 11 p.m.10 a.m. 66 Penza region
b
11 p.m.6 a.m.
25 Bryansk region 10 p.m.8 a.m. 67 Republic of Kalmykia 11 p.m.6 a.m.
26 Irkutsk region 10 p.m.8 a.m. 68 Republic of Mordovia 11 p.m.6 a.m.
27 Nizhni Novgorod regionb 10 p.m.8 a.m. 69 Republic of Altai 12 a.m.7 a.m.
28 Republic of Marij El 10 p.m.8 a.m. 70 Sverdlovsk region 12 a.m.7 a.m.
29 Republic of Sakha (Yakutia) 10 p.m.8 a.m. 71 Saratov region
b
12 a.m.6 a.m.
30 Ryazan region 10 p.m.8 a.m. 72 Republic of Khakasia 2 a.m.7 a.m.
31 Belgorod region 11 p.m.9 a.m. 73 Altai territoryb no restrictions
32 Republic of Adygeya 11 p.m.9 a.m. 74 Kaliningrad region no restrictions
33 Amur region
b
11 p.m.8 a.m. 75 Karachaevo-Chercessian Republic no restrictions
34 Arkhangelsk region 11 p.m.8 a.m. 76 Khabarovsk territory no restrictions
35 Kaluga region
b
11 p.m.8 a.m. 77 Khanty-Mansijsk autonomous district -
Yugraa no restrictions
36 Kursk region 11 p.m.8 a.m. 78 Kostroma region no restrictions
37 Lipetzk region
b
11 p.m.8 a.m. 79 Krasnoyarsk territory
b
no restrictions
38 Novgorod region 11 p.m.8 a.m. 80 Kurgan region
ab
no restrictions
39 Oryol region 11 p.m.8 a.m. 81 Omsk region no restrictions
40 Perm territoryb 11 p.m.8 a.m. 82 Samara region no restrictions
41 Republic of Bashkortostan 11 p.m.8 a.m. 83 Smolensk regionb no restrictions
42 Republic of Komi
b
11 p.m.8 a.m.
a Regions not included in the analysis of regional per capita sales.
b Total of 32 regions included in the Russian Longitudinal Monitoring Survey.
Note. The data in this table are from the Centre for National Alcohol Policy, available at:
http://www.alcomarket.info/CRNAP/print.asp?NewsId=153203; the Information Agency “Russian News,” available at: http://ru-
news.ru/art_desc.php?aid=4783; websites of regional authorities.
–––––– IJADR 3(3) ––––––
... There are a number of studies of alcohol use and its effects using Russian data (Nemtsov, 2000;Denisova, 2010;Bhattacharya et al., 2013;Kueng and Yakovlev, 2020;Yakovlev, 2013;. There is also literature on the accompanying or the same restrictive Russian policies (Neufeld & Rehm, 2013;Pridemore et al., 2013;Kolosnitsyna et al. 2014; with results supporting their effectiveness as a means to decrease alcohol consumption. Kolosnitsyna et al. (2014; explored the same policy, contrasting 2009 with 2010 even though the restrictions had been gradually imposed since 2005, and did not examine the substitution of surrogates not under restriction. ...
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... To determine the effect of interest, I apply difference-in-differences and synthetic controls. Unlike other studies which examine the same policy (Kolosnitsyna et al., 2014;, this paper examines the effect of the restrictions on longitudinal data from 1996-2011, that is, from the years in which none of the regions were under restrictions to the time in which all the regions were under the restrictions. ...
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Lifetime patterns of income may be an important driver of alcohol use. In this study, we evaluated the relationship between long-term and short-term measures of income and the relative odds of abstaining, drinking lightly-moderately and drinking heavily. We used data from the US Panel Study on Income Dynamics (PSID), a national population-based cohort that has been followed annually or biannually since 1968. We examined 3111 adult respondents aged 30-44 in 1997. Latent class growth mixture models with a censored normal distribution were used to estimate income trajectories followed by the respondent families from 1968 to 1997, while repeated measures multinomial generalized logit models estimated the odds of abstinence (no drinks per day) or heavy drinking (at least 3 drinks a day), relative to light/moderate drinking (<1-2 drinks a day), in 1999-2003. Lower income was associated with higher odds of abstinence and of heavy drinking, relative to light/moderate drinking. For example, belonging to a household with stable low income ($11-20,000) over 30 years was associated with 1.57 odds of abstinence, and 2.14 odds of heavy drinking in adulthood. The association between lifetime income patterns and alcohol use decreased in magnitude and became non-significant once we controlled for past-year income, education and occupation. Lifetime income patterns may have an indirect association with alcohol use, mediated through current socioeconomic conditions.
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The neighborhood distribution of education (education inequality) may influence substance use among neighborhood residents. Using data from the New York Social Environment Study (conducted in 2005; n=4000), we examined the associations of neighborhood education inequality (measured using Gini coefficients of education) with alcohol use prevalence and levels of alcohol consumption among alcohol users. Analyses were adjusted for neighborhood education level, income level and income inequality, as well as for individual demographic and socioeconomic characteristics and history of drinking prior to residence in the current neighborhood. Neighborhood social norms about drinking were examined as a possible mediator. In adjusted generalized estimating equation regression models, one-standard-deviation-higher education inequality was associated with 1.18 times higher odds of alcohol use (logistic regression odds ratio=1.18, 95% confidence interval 1.08-1.30) but 0.79 times lower average daily alcohol consumption among alcohol users (Poisson regression relative rate=0.79, 95% confidence interval 0.68-0.92). The results tended to differ in magnitude depending on respondents' individual educational levels. There was no evidence that these associations were mediated by social drinking norms, although norms did vary with education inequality. Our results provide further evidence of a relation between education inequality and drinking behavior while illustrating the importance of considering different drinking outcomes and heterogeneity between neighborhood subgroups. Future research could fruitfully consider other potential mechanisms, such as alcohol availability or the role of stress; research that considers multiple mechanisms and their combined effects may be most informative.
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Using a variety of data sets from two countries, we examine possible explanations for the relationship between education and health behaviors, known as the education gradient. We show that income, health insurance, and family background can account for about 30 percent of the gradient. Knowledge and measures of cognitive ability explain an additional 30 percent. Social networks account for another 10 percent. Our proxies for discounting, risk aversion, or the value of future do not account for any of the education gradient, and neither do personality factors such as a sense of control of oneself or over one's life.