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Can Alcohol Prohibition Reduce Violence Against Women? †


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Violence against women is a critical problem across the world. In this paper, we exploit state and temporal variation in alcohol control in India to examine the impact of prohibition on alcohol consumption and violent crimes against women. We first use detailed household survey data to show that prohibition policies are associated with substantially lower rates of drinking among men and domestic violence. Next, we provide evidence that alcohol prohibition reduces aggregate violence against women in officially reported crime data. The results suggest that policies that restrict access to alcohol may help reduce gender violence.
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Can Alcohol Prohibition Reduce Violence Against Women?
BY Dara Lee Luca, Emily Owens, and Gunjan Sharma*
* Luca: Harvard University and the University of Missouri, John
F. Kennedy School of Government, Mailbox 4, 79 JFK Street,
Cambrige, MA 02138 ( Owens:
University of Pennsylvania, Department of Criminology, 3718 Locust
Walk, Philadelphia PA 19104 ( Sharma:
World Bank, 1818 H Street NW, Washington, DC 20433
I. Introduction
Violence against women is a persistent and
pressing problem in the developed and
developing world; in 2013, the WHO
estimated that roughly 35% of all women have
been victims of physical or sexual violence,
with prevalence rates ranging from 27% in
Europe to over 40% in Africa and South-East
Asia (WHO 2013). The economic
consequences of this particular type of
violence are enormous, particularly in
countries struggling with inequality, poverty,
and low labor force participation rates.
Identifying effective ways to reduce
violence against women has proven difficult.
General improvements in women’s economic
power and social status appear to reduce the
rate at which they are victimized by intimate
partners (Aizer 2012, Stevenson and Wolfers
2006), but these long run, structural shifts in
the societal view of women can be challenging
to mandate through policy.
In this paper, we examine the impact of
alcohol prohibition on intimate and non-
intimate violence against women in India.
Over the past 30 years, alcohol consumption
in Indian has risen dramatically, and binge
drinking in particular has become increasingly
prevalent among the (mostly male) population
of drinkers. In fact, in 2014 the World Health
Organization identified Indian drinkers as
among the most problematic in the world, in
terms of total years of life lost to alcohol
consumption (WHO 2014).
By reducing the availability of alcohol,
Indian governments that restrict alcohol sales
may reduce mortality, crime rates, and overall
physical health (Carpenter and Dobkin 2011),
This may disproportionately benefit women;
survey data consistently suggest that excessive
alcohol consumption is associated with
increased rates of domestic violence and abuse
(Leonard 2005).
Of course, there are many reasons to doubt
that, on net, state level alcohol prohibitions are
optimal for society. For one, prohibiting the
sale of alcohol may not substantively reduce
drinking at all. According to the 2011-2012
National Sample Survey Office report on
alcohol consumption, home-brewed country
Electronic copy available at:
liquor makes up over 70% of total alcohol
consumed in rural states, and in 2012 38% of
low-income Indian drinkers purchased alcohol
on the black market (Ghosh et al. 2012). To
the extent that a significant portion of alcohol
consumed in India is not purchased in the
formal market, the ability of a ban on
commercial transactions to lower drinking rate
is limited.
Further, while the formal market for alcohol
may be relatively small in India relative to
other countries, criminalizing a market may
have important negative social consequences,
including reducing respect for the law and the
perverse potential for increasing violence in
the absence of formal contract enforcement. In
addition, taxation of alcohol sales and
production is an important revenue source for
local governments (Saxena 1999). Hence, this
paper focuses on two questions. First, are
prohibition policies effective in curbing
alcohol consumption in the context of a
developing country? Second, does alcohol
prohibition reduce violence against women?
II. Alcohol Prohibition in India
Alcohol has existed in India for thousands
of years, but prior to British colonial
occupation, drinking was not a central
component of cultural life. As India began to
modernize at the end of the 20th century and
incomes began to rise, alcohol consumption,
particularly of foreign liquor, has grown
exponentially (Saxena 1999). In 2014, the
WHO estimated that 41% of Indian men drank
alcohol, and 12.9% of alcohol consuming
males report episodic binge drinking.
Alcohol regulations are set at the state level
in India, and statutes governing alcohol
consumption and sales diverge greatly across
states. This variation is in part driven by a
number of cross-state differences, including
westernization, urbanization, and per capita
income as well as the political power of
Muslim versus Hindu organizations. As a
result, there is much more large-scale
variation in alcohol control than in the United
States or Canada; Gujarat has prohibited the
sale of alcohol since 1980, and five states:
Andhra Pradesh, Haryana, Mizoram, Orissa,
and Tamil Nadu, have all enacted and/or
repealed bans on the commercial sale and
production of alcohol over the past 30 years.
III. Data and Empirical Strategy
We utilize a number of datasets to
investigate the impact of prohibition on
alcohol consumption and violence against
women. First, we collected from each state the
specific laws pertaining to prohibition of
alcohol (sales and/or consumption) and their
changes over time to compile a panel dataset
documenting the evolution of prohibition
status for 27 major states from 1980 to 2010.
Next, to examine the impact of prohibition on
individual behavior, we rely on the rich
microdata in the 1998-1999 and 2005-2006
rounds of the Indian National Family Health
Survey (NFHS), a large-scale, nationally
representative household survey. The dataset
contains information on both alcohol
consumption of household members, and a
subset of women was asked about their
experience with and attitudes towards intimate
partner violence. Finally, we supplement our
individual-data analysis using state-level
administrative crime data from the Indian
National Crime Records Bureau (NCRB) for
the years 1980 to 2010. We focus on crimes
targeted towards women, including rape,
sexual molestation, sexual assault, cruelty by
husband and relatives, accidental deaths by
fire, and dowry deaths.
We begin our analysis by first examining
the effect of prohibition on drinking behavior
of husbands using a linear probability model.
(1)    
      
  
There is growing evidence that intimate partner homicides or
self-immolation suicides caused by domestic abuse are often
disguised as fire-related accidents. Conflicts over dowries are also
frequently linked to domestic violence.
where are survey year fixed effects,
 is a binary variable equal to
one if state s has a blanket alcohol ban in
survey year y,  and  include a host of
socio-demographic characteristics of the
husband and wife belonging to household h,
including their age, education, religion, and
whether he or she works in a white-collar
occupation. In some specifications, we include
variables to help capture the wife’s bargaining
power within the household, including
whether she has money of her own that she
can control and whether she believes that her
spouse is justified in beating her if he suspects
her of being unfaithful. Along the same vein,
we attempt to proxy for the wife’s relative
wage (since actual wage data are not
available) by including the spousal age and
education gap, both as ratios and as fixed
effects. Because none of the states changed its
prohibition status across the two sample
waves, we include a matrix of state level
controls , to capture systematic differences
between states that could be correlated with
both drinking and violence behaviors,
including the state literacy rate, urbanization,
per capita GDP, the unemployment rate,
police and police expenditure per capita, the
percent of adults who are male, and the state
health and education expenditure per capita.
We then examine the reduced form impact
of prohibition on domestic violence:
(2)     
    
 
where the only difference from Equation (1) is
that the dependent variable is now the
likelihood that the wife reports being beaten
by her husband.
Finally, the main estimating equation in the
state-level analysis is as follow:
     
where are year fixed effects,
 is equal to one if state s has a
prohibition policy in year y and  is the
same matrix of state-level time-varying
controls used in equations (1) and (2), minus
state expenditure measures which are not
available for the entire time period. The
benefit of tracking aggregate crime over a
longer time horizon is that we can also include
a set of state fixed effects in these models.
We cluster standard errors at the state level in
all three regression models.
IV. Empirical Results and Discussion
The results from estimating Equation (1)
and (2) are reported in Table 1.
[Insert Table 1 Here]
Panel A examines the pooled cross-sectional
relationship between the husband’s likelihood
to drink and whether the state has a blanket
prohibition policy in place. Unconditionally,
husbands who are legally prohibited to drink
are roughly 14 percentage points less likely to
drink, compared to a sample mean of roughly
This estimate is essentially unchanged
once we control for state level demographic
characteristics in Column 1. In the next
column we add individual characteristics of
the husband and wife. Column 3 includes
controls for the spousal age and schooling
ratios to help capture the wife’s bargaining
power. We then experiment with different
specifications to account for potential non-
linear effects of the ages of the husband and
wife, as well as the wife’s relative age and
education. In Column 4, we enter the husband
and wife’s 5-year age groups as fixed effects
and also allow for their interaction; the
estimate on prohibition remains similar and
statistically significant. Finally, in Column 5,
we control for the age and education gap
(measured as husband age/schooling wife
age/schooling) as fixed effects.
We find a
Note this is 10 percentage points lower than the WHO survey,
conducted a decade later.
Entering the age and spousal difference in ages as linear
variables gives similar results.
strong first stage relationship across all
specifications husbands living in dry states
are about 12 percentage points less likely to
drink, a 40% reduction in alcohol
consumption rates.
Regression results from estimating Equation
(2) are reported in Table 1 panel B. The
specifications follow in the same order as in
panel A, so that the only difference here is that
the dependent variable is the likelihood that
the wife reports domestic violence. In all
specifications, we find that prohibition is
associated with a statistically significant
change of -8 to -9 percent points in the
likelihood of the husband beating his wife.
The mean rate of domestic violence is around
18%, so this is close to a 50% reduction.
We then extend our analysis by examining
the effect of prohibition on other types of
violence against women using state-year panel
data. Not only does this give us a broader
picture of violence against women, but we can
allow for time invariant differences in
violence and alcohol policy across areas - five
states either enact or repeal prohibition during
this longer time period. We divide the analysis
into two parts: we first focus on crimes that
involve non-fatal violence (cases of cruelty by
husbands and relatives, sexual molestation,
sexual harassment, and rape), and then turn to
crimes that involve non-fatal violence
(suicides, dowry deaths, deaths in fire). The
dependent variables are expressed in rates,
i.e., number of cases per 10,000 people.
[Insert Table 2 Here]
The results, reported in Table 2, provide
additional evidence that prohibition may be
effective in reducing both non-fatal and fatal
crimes against women (Column 1). In
particular, it appears that prohibition is
associated with a statistically significant
reduction in the rates of cruelty by husbands
and sexual harassment. In aggregate,
prohibition is associated with a reduction of
approximately 400 crimes against women per
10,000 people, which is close to a 25 percent
V. Concluding Remarks
In this paper, we examine the impact of
prohibition on alcohol consumption and
violence against women in India. Using
individual level survey data on the alcohol
consumption and exposure to domestic
violence, we find evidence that state level
bans on the commercial sale of alcohol are
associated with substantial reductions in the
likelihood of male drinking as well as
domestic violence. Further, we provide
evidence that alcohol prohibition reduces
aggregate violence against women in officially
reported crime data.
Of course, we caution against interpreting
these results as unambiguous support for
prohibition as there are potential social costs,
including lost state revenue, increased demand
for illicitly produced alcohol, and potential
erosion of support for legal regulations in
areas where the legitimacy of the state is
already tenuous. However, the results of this
paper suggest that regulations that restrict
access to alcohol may help reduce gender
VI. References
Aizer, Anna. 2010. “The Gender Wage Gap
and Domestic Violence” American
Economic Review, 100(4):1847-1859.
Carpenter, Christopher, and Carlos Dobkin.
2011. “The Minimum Legal Drinking Age
and Public Health” Journal of Economic
Perspectives, 25(2): 133-156.
Donald, Stephen G. and Kevin Lang. 2007.
“Inference with Difference-in-Differences
and Other Panel Data” Review of
Economics and Statistics, 89(2): 221-233.
Ghosh, Santanu, Amrita Samanta, and
Shuvankar Mukherjee. 2012. “Patterns of
Alcohol Consumption among Male Adults it
a Slum in Kolkata, India.” Journal of
Health, Population, and Nutrition, 30(1): 73-
Leonard Kenneth E. 2005. “Alcohol and
intimate partner violence: when can we say
that heavy drinking is a contributing cause
of violence?” Addiction 100: 422–5.
Saxena, Shekhar. 1999. “Country Profile on
Alcohol in India” in L. Riley and M.
Marshall Alcohol and Public Health in 8
Developing Countries” Geneva: Substance
Abuse Department Social Change and
Mental Health, World Health Organization:
Stevenson, Betsey and Justin Wolfers. 2006.
“Bargaining in the Shadow of the Law:
Divorce Laws and Family Distress”
Quarterly Journal of Economics 121(1) 267-
World Health Organization (2014) “Global
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Geneva: WHO Press.
World Health Organization (2013) “Global
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Table 1 The Impact of Prohibition on Alcohol Consumption and Domestic Violence
Dependent Variable
Panel A
Panel B
Husband Controls
Wife Controls
Bargaining Controls
Husband Age Group x Wife Age
Group Fixed Effects
Age and Education Gap Fixed
Notes: Standard errors presented in parentheses are clustered by state, using the Donald and Lang (2007) two step adjustment for the small
number of clusters (27). All regressions include survey year fixed effects, and state level controls in all regressions include annual measures of
unemployment rate, literacy rate, percent urban, GDP per capita, and police and police expenditure per capita, and state health and education
spending per capita. Individual controls for husband and wife includes age, years of schooling, whether he or she belongs to a white collar
occupation, household size, urban residence, religion, and number of children.. To control for her household bargaining power, we include the
wife’s attitudes towards domestic violence, whether she has money of her own that she controls, and the wife to husband age and schooling
*** Significant at the 1 percent level.
** Significant at the 5 percent level.
* Significant at the 10 percent level.
Table 2 The Impact of Prohibition on Other Crimes Against Women
Panel A
Panel B
Fatal Violence
Dowry Deaths
Deaths in Fire
All Violence
Notes: Standard errors presented in parentheses are clustered by state.. All regressions include state and year fixed effects, and are weighted by
state population. Controls include annual measures of unemployment rate, literacy rate, percent urban, GDP per capita, and police per capita.
*** Significant at the 1 percent level.
** Significant at the 5 percent level.
* Significant at the 10 percent level.
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