Running head ARTICLE REVIEW .docx

Running head: ARTICLE REVIEW
1
ARTILCE REVIEW
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Law Review Article
University of Michigan-Dearborn
Leila Bazzi
3/20/19
Article Analysis
The title of the article is “The Gender Wage Gap and Domestic
Violence”. The author of the article is Anna Aizer. Also, the
name of the Law Review in which the source was published is
called, American Economic Review. The source is relevant
since it was published in the year 2010. Furthermore, this is a
dynamic topic that changes with time. Therefore, it is essential
to use recent articles to ensure that the latest trends in the
gender wage gap and domestic violence are captured. The
article has not been updated in the last nine years. As mentioned
before, the gender wage gap and domestic violence are sensitive
topics that require the most current, up-to-date information. As
a result, I would need sources that were published in the last

nine years to make the information relevant and feasible.
The authority of the article is excellent. The author of the
article is Anna Aizer, a renowned author who has published
several articles that relate to issues that affect women in the
United States of America and other parts of the world.
Importantly, the author is a Ph.D. holder in three different
fields; organizational behavior, human psychology, and
leadership. The qualifications and experience of the author
make the source credible and reliable. Notably, her article is
retrieved from one of the most legit and trustable websites,
National Center for Biotechnology Information. The website
URL ends in “.gov”, meaning this site is exclusively owned and
operated by the government.
The government website does not give information that has been
verified by different agencies and scholars. Therefore, anyone
reading the article should not doubt about biasness or
misleading information. In many cases, students are warned
about information obtained from Wikipedia and blog sites; this
is not the case here. I selected this article due to my natural
interest on domestic violence which goes hand-in-hand with my
topic, the gender wage gap. I think this article is appropriate for
writing a paper based on credible university-level research due
to the mere fact that it was found on a site operated by the U.S
government. With that being said, the article’s information is
credible enough to rely on.
Moreover, the information and claims that the article provides
are supported by multiple citations and evidence. For instance,
as stated, “disadvantaged women face much higher risks of
abuse. Women with annual income below $10,000 report rates
of domestic violence five times greater than those with annual
income above $30,000 (Bureau of Justice Statistics 1994).” In
this statistic, the author supports the claim by citing and
directing the reader to the secondary source she used.
Furthermore, there are several examples that the article provides
to drive her point home as well as prove the reliability of the
source. In a nutshell, I would say that both the author and the

publisher are not biased. They use an academic convention
language to support their argument to win the trust of the
reader.
Summary of the Article
The article discusses the gender wage gap and domestic
violence. The author claims that domestic violence mostly
affects poor women. The purpose of the study is to investigate
the effects of gender gap wage on domestic violence in the US
(Aizer, 2010). According to the author’s hypothesis, “the
increase in women’s income produces a corresponding decrease
in domestic violence” (Aizer, 2010). However, the vice-versa is
not true: the increase in men’s income escalates domestic
violence in the United States of America. The study took a
qualitative approach where the secondary sources were used to
examine the problem at hand. According to the results, the
reduction in the gender wage gap has a positive impact on
domestic violence (Aizer, 2010). Over the last thirteen years,
the number of domestic violence has significantly reduced due
to new policies that have enacted to reduce the gender wage
gap. The results of the study support the hypothesis formulated
by the author.
References
Aizer, A. (2010). The gender wage gap and domestic
violence. American Economic Review, 100(4), 1847-59.
Bureau of Justice Statistics.1994. “Violence Between
Intimates.” Selected Findings NCJ- 149259.
1847
American Economic Review 100 (September 2010): 1847–1859
http://www.aeaweb.org/articles.php?doi=10.1257/aer.100.4.184
7

Three-quarters of all violence against women is perpetrated by
domestic partners, with poor
women disproportionately affected. The estimated costs of
domestic violence in terms of medi-
cal care and declines in productivity exceed $5.8 billion
annually (Centers for Disease Control
2003). In this paper I examine the impact of the gender wage
gap on levels of domestic violence
in the United States. An economic theory of household
bargaining that incorporates violence
predicts that increases in a woman’s relative wage increase her
bargaining power and lower levels
of violence by improving her outside option. To test the
predictions of this theory, I estimate the
impact of the gender wage gap on violence against women by
exploiting exogenous changes in
the demand for labor in female dominated industries relative to
male dominated ones. I find that
decreases in the wage gap reduce violence against women.
This research addresses a number of limitations in existing
work. First, most previous studies
of the relationship between women’s income and domestic
violence fail to establish a causal rela-
tionship by failing to account for the potential for omitted
variable bias or reverse causality. Even
the handful of papers that do consider this potential endogeneity
focus largely on a woman’s own
wage when a household bargaining model suggests both that a
woman’s relative wage matters
and that potential, not actual, wages determine bargaining
power and levels of violence. Finally,
previous work is based on survey data which are prone to
nonrandom underreporting and are not
consistently collected over time.

To overcome these shortcomings, I employ two strategies. First,
I develop a new measure of
violence based on administrative data: female hospitalizations
for assault. These data represent
an improvement over individual survey data because they do not
necessarily rely on self-reports
of violence, are consistently collected over a long period of
time, and include the universe of
women in California (roughly 15 million individuals). Second,
to overcome the endogeneity of
individual wages and account for the fact that theory predicts
that potential, not actual, wages
affect violence, I analyze the impact of the wage gap as a
function of local demand for female
and male labor on domestic violence. To do so I take advantage
of the fact that certain industries
have traditionally been dominated by women (e.g., services) and
others by men (e.g., construc-
tion) to create sex-specific measures of prevailing local wages
based on the industrial structure
of the county and statewide wage growth in industries dominant
in each county. Constructed in
this way, this measure of the gender wage gap reflects sex-
specific labor demand (see Timothy
Bartik 1991; Olivier J. Blanchard and Lawrence F. Katz 1992)
not underlying worker character-
istics in the county which could be correlated with domestic
violence. I find that reductions in
the gender wage gap explain nine percent of the decline in
domestic violence witnessed between
1990 and 2003.
While these findings are consistent with a model of household
bargaining that incorporates
violence, they are inconsistent with sociocultural models of
“male backlash” that predict that as

The Gender Wage Gap and Domestic Violence
By Anna Aizer*
* Department of Economics, Brown University, 64 Waterman
Street, Providence, RI 02912 and NBER (e-mail:
[email protected]). The author thanks Janet Currie, Pedro Dal
Bó, Mark Duggan, Melissa Kearney, and seminar par-
ticipants at Brown University, UC Berkeley Goldman School,
the University of Maryland, and the BU/Harvard/MIT
joint seminar in health economics for helpful comments and
suggestions. This research project was supported by NSF-
SES 0648700 and NIH RO3HD051808-01A2.
SEPTEMBER 20101848 THE AMERICAN ECONOMIC
REVIEW
women’s wages increase, violence against them increases
because men feel their traditional gen-
der role threatened. They are also inconsistent with the model of
exposure reduction developed
by criminologists that predicts that as the labor force
participation of women increases, violence
against them may decline because women spend less time with
their violent partners. I find that
the reductions in violence occur during nonworking hours,
which is inconsistent with exposure
reduction. These findings shed new light on the health
production process as well as observed
income gradients in health and suggest that in addition to
addressing concerns of equity and
efficiency, pay parity can also improve the health of American
women via reductions in violence.

I. Background on Domestic Violence
A. Prevalence of Domestic Violence and Risk Factors
Every day 14 thousand women in the United States are battered
and four are killed by their
intimate partners. Data on domestic violence from the 1994
National Violence Against Women
survey reveal an annual prevalence of two percent, a lifetime
prevalence of 25 percent and that
intimate partners are responsible for three-quarters of all
violence against women (Patricia
Tjaden and Nancy Thoennes 1998). Disadvantaged women face
much higher risks of abuse.
Women with annual income below $10,000 report rates of
domestic violence five times greater
than those with annual income above $30,000 (Bureau of Justice
Statistics 1994). Black women
are also at significantly greater risk of violence (Callie M.
Rennison and Sarah Welchans 2000).
The National Crime Victimization Survey is the only survey
that allows tracking of domes-
tic violence over time, and these data suggest that reported rates
have declined by 50 percent
between 1993 and 2001, a trend that is likewise present in the
California hospitalization data
analyzed here.
B. Theories of the Relationship between Wages and Violence
Most research on domestic violence has been conducted by
criminologists and sociologists
who have examined domestic violence largely through a
sociocultural lens. Criminologists
have developed a theory of exposure reduction that posits that

the increase in employment
among either men or women will reduce domestic violence by
reducing the time partners spend
together (Laura Dugan, Daniel Nagin, and Richard Rosenfeld
1999). The theory of “male back-
lash” prominent in the sociological literature predicts that as
women’s financial independence
increases, violence against them should increase. According to
Ross Macmillan and Rosemary
Gartner (1999), a wife’s independence “signifies a challenge to
a culturally prescribed norm of
male dominance and female dependence. Where a man lacks this
sign of dominance, violence
may be a means of reinstating his authority over his wife” (p.
949). A theory of male backlash
that predicts that an increase in women’s wages leads to an
increase in violence is problematic
because it ignores the individual rationality constraints faced by
women in abusive relationships.
That is, as their income increases, women are more likely to end
the partnership if transfers
decline and abuse continues.
Economic theories of household bargaining incorporate
individual rationality constraints but
generally do not incorporate violence. In the Appendix I present
a Nash bargaining model in
which utility is a function of consumption and violence, with
the man’s utility increasing in
violence and the woman’s decreasing in violence.1 The main
result is that increasing a woman’s
1 Amy Farmer and Jill Tiefenthaler (1997) present a particular
case of a noncooperative model of domestic violence
in which men have all the bargaining power.

VOL. 100 NO. 4 1849AIZER: THE GENDER WAGE GAP AND
DOMESTIC VIOLENCE
relative wage increases her bargaining power and lowers the
level of violence by affecting her
outside option. This is inconsistent with the model of male
backlash.
Two additional implications of the household bargaining model
are worth highlighting as they
inform the empirical analysis. First, relative wages matter.
Second, it is the potential wage that
determines one’s outside option, not the actual absolute wage.2
This suggests that one should
focus on relative labor market conditions for women, not
women’s actual absolute wages, in the
analysis. This also implies that improving labor market
conditions for women will decrease vio-
lence even in households where women do not work (Robert A.
Pollak 2005).
C. Previous Empirical Work on Wages and Violence
The pioneering study of the relationship between women’s
income and violence is Richard
Gelles (1976), who finds that the fewer resources a woman has,
the less likely she is to leave an
abusive relationship. This work and many others that followed
did not consider the potential
endogeneity of women’s income in this context. Specifically,
omitted variables associated with
women’s wages such as education might explain the negative
relationship with violence, or the
relationship might simply reflect reverse causality—declines in

abuse may increase a woman’s
productivity and earnings.
More recently, economists have employed structural methods or
used panel data to overcome
the problem posed by endogenous wages. Audra J. Bowlus and
Shannon Seitz (2006) use struc-
tural methods to estimate a negative impact of female
employment on abuse. Helen V. Tauchen,
Ann D. Witte, and Sharon K. Long (1991) and Farmer and
Tiefenthaler (1997) utilized panel
data on victims of domestic violence to examine the impact of
changes in a woman’s income
over time on violence. Panel data enables one to overcome the
potential for bias from omitted
variables if they are time invariant but does not rule out the
potential for reverse causality. Also,
results based on a small sample of women in shelters may not be
generalizable. The only experi-
mental evidence on the impact of women’s economic status on
domestic violence comes from
a randomized intervention combining microfinance with
violence education in South Africa.
Women randomized to receive the intervention experienced a 55
percent drop in domestic vio-
lence relative to the control group (Paul Pronyk et al. 2006).3
But none of the existing work captures the importance of
relative female labor market condi-
tions, which theory predicts can explain a decline in domestic
violence even in households where
women do not work. In this paper I provide the first causal
estimates of the impact of women’s
relative labor market conditions on domestic violence based on
a large and representative sample
of women that would capture effects in all households. I discuss

the threats to identification and
my strategies to address them in the next section.
II. Identification of the Impact of the Wage Gap on Domestic
Violence
There are two main threats to identification of the impact of the
gender wage gap on domestic
violence. The first is the lack of objective measures of domestic
violence collected consistently
2 This is due to the fact that a woman’s earnings at her threat
point determine her bargaining power, and earnings at
the bargaining equilibrium do not necessarily equal earnings at
the threat point. Pollak (2005) provides an example of
a married woman who does not work (zero wages) at the
cooperative equilibrium but who would work in the event of
the dissolution of the marriage.
3 Other related work on domestic violence more generally but
not the relationship between violence and income
include Dugan, Nagin, and Rosenfeld (1999), Francis Bloch and
Vijayendra Rao (2002), Betsey Stevenson and Justin
Wolfers (2006), Thomas Dee (2003), Angela Fertig, Irwin
Garfinkel, and Sarah McLanahan (2004), and Jennifer Nou
and Christopher Timmins (2005).
REVIEW
over time. Previous work has found that self-reported measures
of domestic violence are under-
estimates, and that the degree of misreporting is nonrandom
(Mary Ellsberg et al. 2001). Even if

one could accurately model the degree of underreporting, there
exists no panel of self-reported
domestic violence that would enable one to estimate the impact
of changes in labor market con-
ditions. Utilizing a cross-section of data is problematic because
of the difficulty controlling for
multiple differences (in addition to labor market conditions),
across geographic regions that
might bias estimates.
The second threat to identification is the difficulty constructing
measures of relative labor
market conditions that do not reflect the underlying
characteristics of male and female workers
which could be a function of underlying violence (abused
women are less productive) or unob-
servables that might be correlated with violence (e.g.,
education). Thus, for purposes of identifi-
cation, one ought to construct a measure of prevailing female
(male) wages that reflects only the
exogenous demand for female (male) labor.
To address these two threats to identification I construct new
measures of both violence
against women and relative wages. The measure of violence
against women is derived from
administrative data on female hospitalizations for assault for the
state of California. This mea-
sure is collected consistently over a long period of time (1990–
2003) and contains detailed geo-
graphic identifiers that enable one to characterize the local
labor market and include local market
(county) fixed effects. In addition, this measure does not rely on
self-reports of domestic violence.
I include all hospitalizations for assault based on physician
classification of injury. As such, the

measure is not a function of self-reported battery. However, this
measure will also reflect non-
intimate violence. To the extent that three-quarters of violence
against women is intimate and I
can control for trends in nonintimate violent crime in the
regressions, any potential bias from this
measurement error is limited.4
The measure of relative wages is constructed so as to reflect
exogenous demand for female
and male labor and is based on the index of labor demand
originally proposed by Bartik (1991)
and subsequently used by Blanchard and Katz (1992), John
Bound and Harry J. Holzer (2000),
Hilary W. Hoynes (2000), and David H. Autor and Mark G.
Duggan (2003). This strategy takes
advantage of a history of sex and race segregation by industry
that is well established (Kimberly
Bayard et al. 1999) to construct measures of local labor market
wages of women (men) that
are based on wage changes in industries dominated by women
(men). For example, data for
California reveal that 72 percent of service industry employees
are women, while 90 percent of
those employed in the construction industry are men.
Average annual wages are calculated by gender and race in each
county as follows:
(1) __ w grcy = ∑
j
γgrcj w−cyj
where g indexes gender, r race, c county, y year, and j industry.

γgrjc is the proportion of female (or
male) workers with no more than a high school diploma of a
given race working in industry j in
county c (from the 1990 Census). I focus on low-skilled workers
because violence is much more
prevalent among this group (see Table 1). This proportion (γ) is
fixed over this period so that
changes in the wage do not reflect selective sorting across
industries over this period. W−cyj is the
annual wage in industry j in the state except for county c in year
y from the Bureau of Economic
4 This measure will also capture only severe violence. To the
extent that there is less discretion in the use of hos-
pitalization in the case of severe violence, we limit
measurement error by focusing on hospitalizations. However,
one
might be concerned that this captures violence against those
women who have no other source of medical care. In later
regressions I focus on hospitalization for assault during the
weekend, when there are clearly very few, if any, other
sources of medical care, and the results remain.
DOMESTIC VIOLENCE
Analysis annual survey of employers. By measuring prices over
all counties in the state except
the focal county, I remove from the measure any changes in
industry wages that might be caused
by changes in the underlying characteristics of workers in the
county. With the wage constructed
in this way, identification comes from the fact that counties
with many workers in industries

characterized by large, statewide wage growth will experience
larger increases in average wages
than counties with many workers in low–wage growth
industries.5
This inflation-adjusted measure of the female/male wage ratio
increases 3.6 percentage points
between 1990 and 2003 from 0.945 to 0.981. Over this period,
the true wage ratio increased from
70 to 75.5 percent (5.5 percentage points) among low skilled
workers in California. We can think
of the true wage gap as composed of a between-industry and a
within-industry component, with
the wage gap measured according to (1) representing the
between-industry wage gap. It is inter-
esting to note that even though within-industry differences in
wages (between men and women)
explain more of the total wage gap than between-industry
differences in levels, between-industry
differences explain more of the change in the wage gap over the
period 1990–2003.
III. Empirical Results
A. Descriptive Analysis—Prevalence/Trends in Domestic
Violence
Descriptive analysis of the prevalence and trends in domestic
violence over this period yields
a number of interesting results (Table 1). The rate of female
hospitalization for assaults (per
100,000 women) declined nearly 70 percent from 39 to 12. But
this downward trend reflects both
declines in underlying violence and declines in hospital
utilization more generally. To control for
the latter, I also present the decline in assaults regression-

adjusted for secular trends in hospital-
ization in the fourth row of Table 1. This adjusted measure of
female hospitalization for assaults
still declines markedly over this period, but less so, by 36
percent.
5 I remove military workers from this analysis because they are
unlikely to be represented in the hospitalization data
(since it excludes military and VA facilities), nor are they likely
to be represented in the arrest data, which exclude the
military police.
Table 1—Measures of Violence Over Time and by
Socioeconomic Status
1990 2003 Percent change
Panel A. All violence
Female assaults per 100,000 39.3 12.1 −69
Intimate partner homicide per 100,000 1.6 1.1 −31
Non–intimate partner homicide
per 100,000
18.6 14.0 −25
Assaults adjusted for declines in
hospital use
−36
Panel B. Assaults per 100,000 pregnant women
All 31
Medicaid 59

Private pay 12
< HS 41
College 1.3
REVIEW
As an external validity check, I compare this with the decline in
intimate partner homicides
which criminologists consider a well-defined, well-measured, if
imperfect, estimate of domestic
violence. Intimate partner homicides in California decline by 31
percent over this period (row
2, Table 1) which is very similar to the decline in (adjusted)
female hospitalizations for assault.
It is important to note that violent crime more generally also
declined over this period, though
not as much as domestic violence. For example, nonintimate
homicides in California declined 25
percent over this same period, which is very similar to the 20
percent decline in male hospital-
izations for assault (not shown). In the regression analyses that
follow, I control for both secular
trends in violent crime and hospital utilization more generally
to help identify the impact of the
wage gap on domestic violence.
There are significant differences in these measures of violence
among women—with poor
and less educated women disproportionately affected. Panel B
of Table 1 shows differences in
rates of assaults by insurance status (a proxy for income) and
education for pregnant women in

1990/1991 for whom, because the data are matched with birth
certificate data, we have addi-
tional information. Women on Medicaid, who have income at or
below 200 percent of the federal
poverty line (FPL), are nearly six times more likely to have
been admitted to the hospital for an
assault while pregnant than private pay patients. And while 41
(per 100,000) pregnant women
without a high school diploma are admitted for an assault, only
1.3 pregnant women with a col-
lege degree are.
B. Regression Estimates of the Impact of the Wage Gap on
Domestic Violence—
Main Specification
To estimate the impact of the wage gap on domestic violence,
the following equation is esti-
mated using panel data for the period 1990–2003:
(2) DVcry = α + β1WAGERATIOcry + β2UNEMPcy +
β3INCcy + β4RACEr + β5POPcry
+ β6VIOLENT CRIMEcry + β7 DVcry−1 + γ YEARy +
θCOUNTYc
+ π COUNTY × YEARcy + λRACEr × YEARry + εcry .
Each observation is a county-race-year cell with c indexing
county, r race, and y year. DV refers to
the natural log of female assaults derived from administrative
hospitalization data. Natural logs are
used so that estimates across multiple specifications are
comparable and because significant varia-
tion in the levels of violence within the population suggests that
estimating proportional effects is
more suitable.6 WAGERATIO is the ratio of female to male
wages constructed according to equa-
tion (1).7 UNEMP is the annual unemployment rate in the

county, and INC is the natural log of
per capita income in the county and year. These are included so
that the impact of relative income
can be identified separately from the impact of general
economic conditions in the county. RACE
is a vector of race dummies (black, Asian and Hispanic—white
is excluded). POP is the natural
log of the number of women between the ages of 15 and 44 in
the county of a given race in year
y. VIOLENT CRIME is the natural log of nonintimate
homicides by county, race and year and is
included to control for secular trends in violent crime. County
fixed effects and county and race
6 The results are robust to a linear specification.
7 Examining the impact of relative wages within racial groups
is justified given that interracial relationships are still
relatively rare over this period: 14 percent for 18–19-year-olds,
12 percent for 20–21, and 7 percent for 34–35-year-olds
(Kara Joyner and Grace Kao 2005).
DOMESTIC VIOLENCE
specific linear time trends are included to control for any
unobserved fixed differences between
counties and any county and race-specific linear time trends in
domestic violence, respectively. The
year fixed effects will control for all statewide policy changes
such as welfare reform, expansions in
the EITC, changes in Medicaid eligibility, or state laws
regarding the prosecution of domestic vio-
lence as well as the federal Violence Against Women Act of

1994 that may affect rates of domestic
violence. I also include the natural log of female admissions for
nonassault injuries and the natural
log of male assaults to control for secular trends in hospital
utilization. The latter also likely cap-
tures secular changes in violent crime not captured by
homicides. Finally, in some specifications I
also include lags of the dependent variable (DVcry−1) to
control for any other omitted time varying
characteristics.8 These would include any unmeasured changes
in the underlying composition of
women (or men) in the state that are correlated with domestic
violence in the recent past. All regres-
sions are limited to county-race-year cells with female
population of at least 10,000 to increase
the precision of measures of violence based on moderate to low
frequency events. I also weight all
observations by the female population in the cell.
The results from the main specification are presented in Table
2. For purposes of comparison,
in the first column I present estimates from a regression that
includes only minimal controls
(fixed effects in levels and trends and the natural log of the
female population). The relationship
between the wage ratio and female assaults is very large,
negative, and significant when only
few controls are included. In column 2, I include most of the
controls listed in equation (2) with
the exception of lagged domestic violence. The estimate of β1
(−0.831) implies that an increase
in the ratio of female to male wages significantly reduces the
number of women admitted to the
hospital for an assault. However, the estimate declined by 40
percent from column 1 to column 2,
underscoring the importance of including proper controls to

reduce bias. In column 3 I include
the lag of the dependent variable to control for any other time
varying unobservables not cap-
tured in the extensive set of controls that may bias the results.
The estimated impact declines
only slightly (0.831 to 0.813), suggesting that the controls
included are fairly comprehensive. The
wage gap has no impact on admissions for substance abuse
(column 4), which is included here
as a falsification test.9
To gauge the size of these effects, I calculate how much of the
decline in violence witnessed over
the period 1990–2003 is explained by closing the wage gap by
3.6 percentage points (the actual
decline for this measure over this period). The narrowing of the
wage gap over this period explains
nine percent of the decline in hospital admissions for assault
(controlling for secular trends in
hospitalization). In column 5, I present estimates of the impact
of the wage gap on the natural log
of male assaults. The coefficient estimate (−0.257) is only 30
percent of that for female assaults
and is statistically insignificant. While we would expect this
estimate to be smaller, we would not
necessarily expect it to be zero. Work on domestic violence
conducted by criminologists has found
that interventions aimed at reducing domestic violence often
lead to significant declines in men
assaulted by their partners in self-defense (Dugan, Nagin, and
Rosenfeld 1999).10
Because an increase in women’s wages is likely to be
accompanied by an increase in female
employment, finding that domestic violence falls as female
wages rise (relative to men’s) may be

8 It’s well established that fixed effects models with lagged
dependent variables are biased for small (“fixed”) T
(Stephen Nickell 1981), and this bias can be approximated by
−(1 + β7)/(T − 1). However, the purpose of including
lagged domestic violence is only to show that the coefficient on
the wage ratio is unchanged, thereby providing addi-
tional evidence that the estimate of the impact of relative wages
on violence does not suffer from omitted variable bias.
9 I also estimate the impact of the wage ratio on female
hospitalizations for car crashes and suicide attempts—both
estimates are small and statistically insignificant.
10 Anna Aizer and Pedro Dal Bó (2009) also provide evidence
that strengthening the prosecution of batterers results
in a decline in violence against men killed by their partners.
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evidence of either a bargaining story or exposure reduction.11
To test whether exposure reduction
is responsible for these findings, I estimate the impact of
changes in the wage ratio on assaults
that occurred during the weekday versus the weekend. To do so
I interact the wage ratio with a
dummy indicating whether the assault occurred during the
weekend for a subset of the data that
includes information on day of the week.12 The estimates
presented in the last column of Table 2
suggest that all the decline in domestic violence as a result of
the falling wage gap occurs during
the weekend, which is inconsistent with the exposure reduction

hypothesis. This result is also
reassuring if one were concerned that hospitalization rates were
disproportionately capturing
women with no other source of medical care since during the
weekend there are few, if any,
alternatives to hospital care available.
11 This assumes that the substitution effect exceeds the income
effect.
12 Hospital data with information on the day of the week of
admission is available only for years 1990–1996 exclud-
ing 1991. These data indicate that there are more
hospitalizations for assault (and other injuries) during the week
compared with the weekend, but that assaults represent a greater
share of injuries during the weekend (0.07) versus
the week (0.05).
Table 2—Impact of Wages on Domestic Violence—Main
Specification
ln(female
assaults)
ln(female
assaults)
ln(female
assaults)
ln(drug
admissions)
ln(male
assaults)

ln(female
assaults)
(1) (2) (3) (4) (5) (6)
Panel A. Ratio of wages
Female/male wage −1.469 −0.831 −0.813 −0.023 −0.257 0.119
[0.673] [0.313] [0.317] [0.072] [0.284] [0.562]
Female/male wage × weekend −1.15
[0.444]
Observations 984 982 982 887 982 616
R2 0.91 0.95 0.96 0.99 0.99 0.96
Panel B. Linear difference in wages
Male wage–female wage 0.0047 0.0024 0.0024 0 0.0009
−0.0003
[0.0020] [0.0009] [0.0009] [0.000] [0.0008] [0.0017]
(Male-female wage) × weekend 0.0031
[0.0015]
Observations 984 982 982 887 982 616
R2 0.91 0.95 0.96 0.99 0.99 0.96
County, year, race fixed effects Yes Yes Yes Yes Yes Yes
County and race specific linear time
trends
Yes Yes Yes Yes Yes Yes

ln(population), ln(nonintimate
homicides)
Yes Yes Yes Yes Yes
Unemployment rate and ln(per capita
income)
Yes Yes Yes Yes Yes
Lagged dependent variable Yes Yes Yes
ln(nonassault injuries) Yes Yes Yes Yes
ln(assaults opposite sex) Yes Yes Yes Yes
Notes: Robust standard errors clustered on county in brackets.
Column 4 includes data from 1992–2003; column 6
includes data for years 1990, 1992–1994, and 1996 and also
includes the main effect of weekend and interactions
between weekend and unemployment and per capita income.
DOMESTIC VIOLENCE
The results are not sensitive to how the wage gap is defined. In
panel B of Table 2, I redefine
the wage gap to be the linear difference between male and
female wages (male wages–female
wages). The coefficient estimates are smaller because of the
scale of the wage gap defined this
way, but the implied effects are similar to the effects estimated
based on the ratio of wages.
C. Additional Specifications

In this section I present the results of a number of alternative
specifications that corroborate a
causal interpretation of the main results. First, I present
empirical evidence that the measure of
the wage ratio does not reflect changes in underlying
characteristics of the work force that might
occur if there were selective in-migration to high female wage–
growth counties (e.g., those with
a growing service sector). I do so by comparing the above
estimates of equation (2) with esti-
mates that include controls for compositional changes in the
county to capture any selective in-
migration. In the Appendix I also present estimates of the
determinants of female (male) wages
and find that changes in underlying composition of the
population do not affect these measures.
Second, I present the results of regressions in which I enter
male and female wages separately
to test the hypothesis that it is the relative wage that matters
and that the relative wage measure
does not simply reflect changes in average wages. Third, I
instrument for relative wages in the
county using statewide employment growth in industries
dominant in the county. This instru-
ment is very similar to the measure of relative demand used in
the main specification (in fact, the
identifying source of variation is the same), but it has the
advantage of being the exact measure of
labor demand used previously, though in different settings.
Finally, I present estimates in which
I identify the impact of changes in the wage ratio based on an
alternative source of variation:
changes over time in the industrial composition of the county.
Additional Controls.—I include additional controls to address
two potential concerns. The

first is that changes in the characteristics of men and women in
the county correlated with both
violence and the wage gap might bias the estimates. This would
occur if areas with a declin-
ing wage gap were characterized by selective in-migration of
people with a lower propensity
for domestic violence. Though I previously included the lag of
the dependent variable (Table 2)
which likely captures any changes in the underlying
characteristics of the county that could be
correlated with both wages and violence, to further address this
concern I include additional
controls. These controls include education, specifically female
and male college enrollment in
all public colleges in California by race, county and year,13
foreign immigration by county and
year, and incarceration flows (number released–number
detained) defined by county, race, and
year. These three measures (education, immigration, and
incarceration) were selected because
they represent the most significant determinants of individual
wages that are also likely to be
correlated with violence: more educated women earn more and
are less likely to be the victims of
violence, immigrant women earn less and are less likely to avail
themselves of law enforcement
and domestic violence services, and men with a criminal
background earn less and are more
violent. In addition, these three measures are available at the
county-race-year level (with the
exception of immigration which does not include race) unlike
data from the Census which would
require interpolations for the intercensal years, adding
measurement error and attenuation bias.
The second concern relates to the possibility that changes in the

wage gap might be correlated
with changes in access to nonhospital medical care which might
reduce reliance on the hospital.
This could occur if the closing of the wage gap were correlated
with increases in female political
13 This includes all community colleges, California State, and
University of California campuses.
REVIEW
power which might lead to allocation of more public resources
to women. To address this I con-
trol for the number of primary care clinics per 1,000 women in
the county.
The inclusion of these controls in Table 3 does not change the
main result. In fact, inclusion of
the controls slightly increases the point estimates of the impact
of the wage ratio on assaults. In
addition, none of the additional controls has a significant
impact on domestic violence, which is
likely due to the extensive set of controls included in the main
specification.
Female and Male Wages Entered Separately.—As a further test
of the theory that relative
wages affect the level of domestic violence, I enter male and
female wages separately in the
regression (column 1, Table 4). The results are consistent with
previous results and with the the-
ory: a rise in female wages holding male wages constant reduces
domestic violence, while a rise

Table 3—Impact of Wages on Domestic Violence—Controls for
Labor Supply
Ln(female assaults)
Female/male wage −0.871
[0.381]
Black −21.76
[21.378]
White −44.852
[27.240]
Hispanic −36.008
[18.274]
Unemployment rate 0.878
[2.600]
ln(per capita income) 0.296
[0.478]
ln(nonintimate homicides) 0.017
[0.028]
Incarceration flows per 10,000 males 0
[0.001]
ln(immigration) −0.015
[0.076]
ln (female students) 0.099
[0.208]
ln (male students) −0.146

[0.275]
ln(female population) 0.252
[0.180]
ln(primary care clinics) 0
[0.119]
Lagged dependent variable 0.016
[0.037]
ln(male assaults) 0.355
[0.066]
ln(female nonassault injuries) 0.453
[0.112]
Observations 930
R2 0.96
County, year, and race fixed
effects as well as county and race specific linear time trends
also included.
DOMESTIC VIOLENCE
in male wages, holding female wages constant, increases
domestic violence (−0.781 and 0.956,
respectively). The male and female coefficient estimates are
statistically equal in absolute value
and opposite in sign, with F statistics and p-values presented at

the bottom of Table 4; however,
the estimate of female wages is imprecise. These results also
rule out the possibility that the rela-
tive wage measure simply captures increases in average wages.
Instrumental Variable (IV ) Estimates.—While I have argued
and presented evidence that
county level wages measured according to equation (1)
represent exogenous measures of female
and male demand for labor, I also instrument for the county-
level wage ratio using state growth
rates in employment for each industry weighted by county
specific shares in those industries.14
The advantage of this alternative measure is that it is equivalent
to the exogenous measure
of labor demand widely used in the labor economics literature
(see Timothy J. Bartik 1991;
Blanchard and Katz 1992; Bound and Holzer 2000; Autor and
Dugan 2003). But the variation in
this measure essentially derives from the same source as the
measure of wages defined according
to equation (1)—statewide changes in demand for workers in a
given industry. As such, we would
expect similar estimates based on the two measures.
The IV results presented in column 2 of Table 4 are similar,
though slightly smaller and less
precise than the estimates from the main analysis. The first
stage, not presented here, is strong:
statewide employment growth in female dominated industries
has a positive and significant
impact on the wage ratio in the county, while statewide
employment growth in male dominated
industries reduces the county wage ratio (F statistic 15.56). I
argue that these results, along with
those that include additional controls for labor supply, support

the exogeneity of the wage mea-
sures used in this analysis and corroborate the main findings.
Redefining the Wage Gap based on Changes in Industrial
Composition of the County.—
Finally, I reconstruct the wage ratio to take advantage of an
alternative source of identifying
14 In these regressions I measure the relative wage ratio in the
county using county wages (not statewide wage) and
instrument for it using industry-level statewide employment
growth measured over all counties except the focal county.
Table 4—Impact of Relative Wages on Domestic Violence:
Alternative Specifications
ln(female assaults) ln(female assaults) ln(female assaults)
ln(drug admissions)
(1) (2) (3) (4)
ln (female wage) −0.781
[0.559]
ln (male wage) 0.956
[0.516]
Female/male wage −0.697 −0.964 0.019
[0.351] [0.355] [0.196]
Observations 982 955 804 776
R2 0.96 0.96 0.96 0.99
Test that female and male wages are equal and opposite in value
F (1, 37) 0.06

p-value 0.81
Column 1 is based on an OLS fixed effect regression; in
column 2, I instrument for the wage ratio using statewide
growth in employment by industry weighted by the county-
specific shares in these industries; in columns 3 and 4 the wage
ratio is derived from changes in the industrial composi-
tion of the county over time; in column 4 are results of a
falsification exercise.
REVIEW
variation: changes in the industrial composition of the county
over time. For this measure I create
time-varying measures of γ (the proportion of women/men
working in a given industry) based
on linear interpolations between 1990 and 2000 Census data and
holding industry wages fixed
at 1990 levels. The result presented in the third column of Table
3 is slightly larger for female
assaults than those based on the main specification and
presented in Table 2.15 However, this
measure is much less arguably exogenous. Appendix Table 1
shows that female and male college
enrollment are more predictive of this measure of wages than
wages that hold industrial structure
fixed, which may indicate endogenous shifts in industrial
composition. This potential endogene-
ity may explain why the point estimate is higher. Finally in
column 4, I present the results of the
falsification exercise based on this alternative measure of
wages: changes in the wage ratio are

unpredictive of substance abuse admissions for treatment.
IV. Conclusion
Over the past 15 years, violence against women has declined as
their employment and earn-
ings have increased. A model of household bargaining presented
in the Appendix that incorpo-
rates violence is consistent with these trends. I provide
empirical support for a causal relationship
between relative labor market conditions for women and
violence. Using new sources of admin-
istrative data that overcome many of the shortcomings of
previous data on domestic violence, I
find that the decline in the wage gap witnessed over the past 13
years can explain nine percent of
the reduction in violence against women. These findings suggest
that in addition to more equi-
table redistribution of resources, policies that serve to narrow
the male-female wage gap also
reduce violence and the costs associated with it. Given existing
evidence that domestic violence
negatively affects child outcomes, reductions in domestic
violence are likely to improve child
outcomes as well. As such, in addition to addressing concerns
of equity and efficiency, improved
pay parity may also generate important intergenerational
effects.
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Autor, David H., and Mark G. Duggan. 2003. “The Rise in the

Disability Rolls and the Decline in Unem-
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Bartik, Timothy J. 1991. Who Benefits from State and Local
Economic Development Policies? Kalama-
zoo, Michigan: W. E. Upjohn Institute for Employment
Research.
Bayard, Kimberly, Judith Hellerstein, David Neumark, and
Kenneth Troske. 1999. “New Evidence on Sex
Segregation and Sex Differences in Wages from Matched
Employee-Employer Data.” National Bureau
of Economic Research Working Paper 7003.
Blanchard, Olivier J., and Lawrence F. Katz. 1992. “Regional
Evolutions.” Brookings Papers on Eco-
nomic Activity, 1992(1): 1–61.
Bloch, Francis, and Vijayendra Rao. 2002. “Terror as a
Bargaining Instrument: A Case Study of Dowry
Violence in Rural India.” American Economic Review, 92(4):
1029–43.
Bound, John, and Harry J. Holzer. 2000. “Demand Shifts,
Population Adjustments, and Labor Market
Outcomes during the 1980s.” Journal of Labor Economics,
18(1): 20–54.
Bowlus, Audra J., and Shannon Seitz. 2006. “Domestic
Violence, Employment, and Divorce.” Interna-
tional Economic Review, 47(4): 1113–49.
Bureau of Justice Statistics. 1994. “Violence Between
Intimates.” Selected Findings NCJ-149259.
Centers for Disease Control. 2003. Costs of Intimate Partner
Violence Against Women in the United

States. Department of Health and Human Services. Atlanta, GA:
Centers for Disease Control.
15 Because of difficulty matching counties in the 1990 and 2000
Census, 20 percent of the sample is lost.
DOMESTIC VIOLENCE
Dee, Thomas S. 2003. “Until Death Do You Part: The Effects of
Unilateral Divorce on Spousal Homi-
cides.” Economic Inquiry, 41(1): 163–82.
Dugan, Laura, Daniel Nagin, and Richard Rosenfeld. 1999.
“Explaining the Decline in Intimate Partner
Homicide: The Effect of Changing Domesticity, Women’s
Status and Domestic Violence Resources.”
Homicide Studies, 3(3): 187–214.
Ellsberg, Mary, Lori Heise, Rodolfo Pena, Sonai Agurto, and
Anna Winkvist. 2001. “Researching Domes-
tic Violence against Women: Methodological and Ethical
Considerations.” Studies in Family Planning,
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Farmer, Amy, and Jill Tiefenthaler. 1997. “An Economic
Analysis of Domestic Violence.” Review of
Social Economy, 55(3): 337–58.
Fertig, Angela, Irwin Garfinkel, and Sara McLanahan. 2004.
“Child Support Enforcement and Domestic
Violence Among Non-Cohabiting Couples.” Princeton
University Center for Research on Child Wellbe-

ing Working Paper 2002-17-FF.
Gelles, Richard. 1976. “Abused Wives: Why do They Stay?”
Journal of Marriage and the Family, 38(4):
659–68.
Hoynes, Hilary W. 2000. “Local Labor Markets and Welfare
Spells: Do Demand Conditions Matter?”
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Joyner, Kara, and Grace Kao. 2005. “Interracial Relationships
and the Transition to Adulthood.” Ameri-
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Macmillan, Ross, and Rosemary Gartner. 1999. “When She
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Reproducedwithpermissionofthecopyrightowner.Furtherreproduc
tionprohibitedwithoutpermission.
The Gender Wage Gap and Domestic ViolenceI. Background on
Domestic ViolenceA. Prevalence of Domestic Violence and
Risk FactorsB. Theories of the Relationship between Wages and
ViolenceC. Previous Empirical Work on Wages and ViolenceII.
Identification of the Impact of the Wage Gap on Domestic
ViolenceIII. Empirical ResultsA. Descriptive Analysis—
Prevalence/Trends in Domestic ViolenceB. Regression
Estimates of the Impact of the Wage Gap on Domestic

Violence—Main SpecificationC. Additional SpecificationsIV.
ConclusionREFERENCES
Cit p_7: Cit p_2: Cit p_6: Cit p_1: Cit p_8: Cit p_5: Cit p_11:
Cit p_18: Cit p_23: Cit p_13: Cit p_20: Cit p_17: Cit p_12: Cit
p_19: Cit p_26: Cit p_16:
DO THE FOLLOWING FOR THE LAW REVIEW ARTICLE
ATTACHED.
1. a) Article title: What is the title and subtitle of your Law
Review Article?
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Inequality Paper Step #2 1
ARTICLE SUMMARY 2
Inequality Paper Step 2
Leila Bazzi

University of Michigan-Dearborn
The Widening Black-White Wage Gap Among Women
The title of this journal article is “The Widening Black-White
Wage Gap Among Women”. The co-authors of this journal
article are J. D. Fisher, & Houseworth. The name of this journal
in which the source was published is the Journal of Economic
Equality.
The women at the age of 30 are likely to be in an income-
generating job. A cohort of ladies of this age were examined
and the disparities in their wages established. Literature has
found that at around this age in a baby boom cohort 1, the wage
gap is estimated at 5 percent in favor of white women while the
gap for their daughters was found to be 15%. First, a cohort of a
woman aged between 26-31 was initially selected and studied,
then later a bigger cohort involving those with 25-55 plus
younger cohorts was used.
It was found out that young women, for both black and white
were more likely to work, as compared to their older
counterparts. In addition, black women were more likely to be
selected for the job and that young white educated women were
unlikely to exit the labor force during childbearing age. White
women could be selected on a positive basis. White women
were more educated than black counterparts (Fisher, &
Houseworth, 2017).
The Gender Wage Gap
The title of this journal article is “The Gender Wage Gap”. The

co-authors of this journal article are F.D. Blau and L.M. Kahn.
The name of this journal in which the source was published is
the Journal of Economic Literature.
The established per capita income variables give little
information on the disparities in the wages between different
gender despite it being a very important factor in the occupation
and industry. The differences in the women workforce as
indicated by per capita values could be attributed to work
interruptions and shorter working hours but discrimination
cannot be discredited in regard to role differences, a division of
labor and occupation difference. This paper seeks to identify the
existing gender pay gap and whether it has an impact on the
difference in the workforce. It was found out that women had
more wage bargaining power as compared to men and a decrease
in wage hit men harder than female counterparts. However,
there was a wage gap between females and males with the same
qualifications. There were no clear reasons as to why the gaps
exist but it observed it could be due to unmeasured productivity,
or compensating differentials while occupational different could
be accounted for by discrimination. In addition, many of the
traditional explanation for wage gap continues to dominate the
reasons but some have reduced in importance (Blau, & Kahn,
2017).
The Power of Lump Sums to Women
The title of this journal article is “The Power of Lump Sums to
Women”. The author of this journal article is G.D. Morton. The
name of this journal in which the source was published is the
Journal of World Development.
This study identifies the influence income contributes to a
peaceful existence in a family and the processes through which
the influence occurs. It looked at the women who are
beneficiaries of two social programs in Brazil. Basically, this
program disbursed a considerable amount of money to pregnant
mothers and looked at how they invested the amount. The study
stipulated that women spend the monthly money to purchase
items like clothing and furniture while giving them lump sum

empowers them. Ideally, the findings of this research concurred
with the stereotypes that feminine property in which purchasing
of assets such as cows and fields. However, unlike monthly
money that encouraged spending on items, lump sums could be
spent in the purchase of assets. On the contrary, women had a
perception that assets they purchased will typically be owned by
men. Therefore, lump sums could help in re-gender households,
bring equality and possibly enable a peaceful coexistence
(Morton, 2019).
References
Morton, G. D. (2019). The power of lump sums: Using
maternity payment schedules to reduce the gender asset gap in

households reached by Brazil’s Bolsa Família conditional cash
transfer. Journal of World Development, 113, 352-367.
Blau, F. D., & Kahn, L. M. (2017). The gender wage gap:
Extent, trends, and explanations. Journal of Economic
Literature, 55(3), 789-865.
Fisher, J. D., & Houseworth, C. A. (2017). The Widening
Black‐White Wage Gap among Women. Journal of
Labour, 31(3), 288-308.
World Development 113 (2019) 352–367
Contents lists available at ScienceDirect
World Development
journal homepage: www.elsevier .com/locate /wor lddev
The power of lump sums: Using maternity payment schedules to
reduce
the gender asset gap in households reached by Brazil’s Bolsa
Família
conditional cash transfer
https://doi.org/10.1016/j.worlddev.2018.08.012
0305-750X/� 2018 Elsevier Ltd. All rights reserved.
E-mail address: [email protected]
1 Other conditions vary by program, but they can include
attending health
education sessions, obtaining prenatal care, or getting an ID
card. For reviews of
conditional cash transfers, see (Valencia Lomelí, 2008; Fizbein,
Schady, & Ferreira,
2009; Lagarde, Haines, & Palmer, 2007; Ranganathan &
Lagarde, 2012; Saavedra &

García, 2012).
2 Bolsa Família officials preferentially sign up women for the
benefit and
card to them; in a household where a woman is not available,
however, a
sign up to receive the money (Lindert, Linder, Hobbs, & de la
Brière, 2007,
Gregory Duff Morton
Bard College, 30 Campus Road, Red Hook, NY 12504, USA
a r t i c l e i n f o
Article history:
Accepted 26 August 2018
Available online 27 September 2018
Keywords:
Bolsa Família
Maternity benefits
Conditional cash transfer
Gender asset gap
Salário Maternidade
Household budgets
a b s t r a c t
Can cash assistance have an influence on gender relations inside
a household? What are the processes
through which this influence occurs? The present article
investigates the everyday uses of money that
women receive from two gender-targeted social programs in
rural Brazil. Bolsa Família is a conditional
cash transfer that disburses money to women every month. The
Maternity Wage is a program that gives
a sizeable lump sum to women when they become pregnant.
Drawing from two years of ethnographic
research in two villages in Northeastern Brazil, I show how
these different payment schedules can lead

to different patterns of investment in assets. I find that women
typically spend monthly cash assistance
on items, like clothing and furniture, that correspond to local
stereotypes about feminine property. By
contrast, lump sums are used by women to purchase income-
generating assets, like cows and fields, that
would normally be held by men. Monthly money reinforces
gendered stereotypes about assets, while
lump-sum money challenges those stereotypes. Lump sums
thereby enable women to become the own-
ers of wealth that generates a flow of income over time. I
identify two key qualities that underlie this
change: a payment’s large size and its unpredictability. These
qualities affect the mental accounting that
beneficiaries use to understand their money and the institutions
through which they save it. By outlining
such processes, the article brings the literature on conditional
cash transfers into dialogue with studies on
the gender asset gap. Lump sums can help to re-gender a
household’s assets. This finding suggests that
cash assistance policy, particularly in the case of conditional
cash transfers, might be able to have an
effect on gender equity by making use of targeted lump sums.
� 2018 Elsevier Ltd. All rights reserved.
1. Introduction
Conditional cash transfers have become important tools for
fighting poverty in middle-income countries. Their importance
derives, in part, from their promise to tackle poverty and gender
inequity at the same time. Conditional cash transfer programs
(CCTs) provide modest, regular cash payments, which are
usually
delivered to women in families with low incomes; in exchange
for the money, children must attend school, receive vaccines,
and

comply with other human-capital ‘‘conditions.”1
In the case of Brazil’s Bosla Família, the world’s largest CCT,
money arrives from the federal government, every month, on a
debit card whose secret code is chosen by the woman receiving
the benefit.2 Policymakers intend for this delivery system to
change
gender relations inside the family (De Brauw, Gilligan,
Hoddinott, &
Roy, 2014, p. 487; Gil-García, 2016, p. 451; Barrientos, 2012,
p. 15;
Adato, De la Briere, Mindek, & Quisumbing, 2000, p. 46).
CCTs thus
raise important questions about what happens to cash once it
reaches a household. Who holds onto the money, who gives
orders
about it, and who spends it? Do households use some of this
money
to buy assets? If so, who owns them?
An outpouring of ethnographic research, in Brazil and beyond,
has begun to answer these questions by documenting the mecha-
nisms through which CCT cash circulates inside households
(Streuli, 2012a,b; Adato et al., 2000; Pires, 2014; Rego &
Pinzani,
2013; Suárez & Libardoni, 2007; Pires and da Silva Jardim,
2014).
issue the
man can
p. 17).
http://crossmark.crossref.org/dialog/?doi=10.1016/j.worlddev.2
018.08.012&domain=pdf
mailto:[email protected]

http://www.sciencedirect.com/science/journal/0305750X
http://www.elsevier.com/locate/worlddev
4 Among survey respondents in rural areas, De Brauw et al.
(2014) find a negative
relationship between receipt of Bolsa Família and women’s
reports that they are the
exclusive decision-makers in household decisions about food,
employment, and
children’s school attendance. Ethnographic evidence from Rio
Branco and Maracujá
(the villages analyzed in the present article) suggests one
possible explanation from
G.D. Morton /World Development 113 (2019) 352–367 353
The present article contributes by focusing on payment
schedule:
how often the money arrives.3 Does it matter that women
receive
this money every month? Would the money have a different
effect
on the household if it came, instead, as a lump sum?
This article is based on ethnography carried out over eighteen
months, from 2011 to 2013, with 51 households receiving Bolsa
Família in the sertão region of rural Brazil. The article relies on
the contrast between Bolsa Família and a different social
program,
the Rural Maternity Wage (Salário Maternidade rural). While
Bolsa
Família enters the household each month, the Maternity Wage is
a
lump sum that women can obtain in a single payment when they
become pregnant.

As it considers the uses of money from these different sources,
the article concentrates on one aspect of household relations:
the
ownership of assets. Ethnography is used to document which
assets – like cows, fields, and appliances – are considered to
belong
to a man or a woman. The article investigates the impact that
social
assistance programs can have on the gendering of these assets.
In
so doing, the article brings CCT scholarship into dialogue with
the literature on the gender asset gap (Deere & Doss, 2006;
Doss,
Deere, Oduro, & Swaminathan, 2014).
I find that women buy assets with some portion of the money
they receive from both Bolsa Família and the Maternity Wage,
but they use the money from each program differently. Bolsa
Famí-
lia’s monthly money often goes towards items that correspond
to
local stereotypes about feminine property – like appliances and
furniture. By contrast, the lump sum from the Maternity Wage
allows women to buy assets that, in these villages, normally
belong
to men – income-generating assets like cows and fields. In other
words, monthly money reinforces gendered stereotypes about
assets, while lump-sum money challenges those stereotypes.
Why do women spend money from the two programs differ-
ently? Anthropological investigation demonstrates that the one-
time lump sum is profoundly disruptive to a household’s normal
budgeting practices. The lump-sum schedule influences people’s
habits of mental accounting and the institutions available to
help
them save. Because of its disruptiveness, I suggest, a lump sum

cre-
ates an opening for household members to reorient the
gendering
of assets.
The article identifies two reasons for the disruptiveness: pay-
ment size and payment unpredictability. First, the Maternity
Wage
delivers a sum whose size is often ten times larger than the per
capita monthly income of a household at the research site, and
because the payment is so large, households cannot save this
money through their habitual savings practices. Instead,
household
members develop new practices of mental accounting. They
make
use of unaccustomed modes of saving—modes such as having
women own masculine assets.
Secondly, the Maternity Wage is granted with great unpre-
dictability. More than half of women who apply for the benefit
are denied. Because of this unpredictability, existing
institutions
do not allow a household to take out credit in anticipation of the
lump sum. If the benefit does arrive, the household must
manage
it as an unanticipated positive shock. Women tend to respond to
this shock by acquiring assets, such as cows and fields, that
serve
as an ongoing source of income. Through the new assets, the
household smooths out the sudden increase in cash by spreading
it over time. These income-generating assets are the property of
3 There have been several scholarly appeals calling for greater
attention to timing
in the analysis of CCTs. Fizbein, Schady and Ferreira noted,
‘‘Timing of payments is
another potentially important design feature. To date, however,

few programs have
experimented in that direction” (2009, p. 133). Rabinovich and
Diepeveen echoed this
theme six years later: ‘‘The impact of dimensions such as the
timing and amount of
transfers and delivery agents and mechanisms remains largely
unexamined” (2015, p.
638).
a woman, which changes intra-household distribution over the
long run.
Lump sums, then, have a special, disruptive capacity to change
the gender asset gap inside the household. This capacity means
that they are potentially powerful tools for social policy.
This article speaks to the extensive literature that documents
the gender effects of conditional cash transfers. CCTs are, at
heart,
gendered policy. The programs were originally motivated by
theo-
retical (Chiappori, 1992; McElroy & Horney, 1981; Lundberg &
Pollak, 1993; Agarwal, 1997) and empirical (Quisumbing &
Maluccio, 2000) research challenging the ‘‘unitary” view that
all
members of a household share a single set of preferences. CCT
pio-
neers found inspiration in studies suggesting that women are
more
likely than men to spend additional income on children
(Thomas,
1990; Hoddinott & Haddad, 1995), although subsequent results
have not always been as tidy (Handa, Peterman, Davis, &
Stampini, 2009; Yablonski and Peterman, 2016; for a review,
see
Yoong, Rabinovich, & Diepeveen, 2012).

More recent empirical work has gone beyond the question of
women’s expenditures on children, examining a range of
gendered
CCT outcomes (van den Bold, Quisumbing, & Gillespie, 2013;
Chap-
ter 3 in Holmes & Jones, 2013). In large-scale surveys,
Mexico’s
Progresa/Oportunidades/Prospera is associated with lower levels
of violence against women (Rivera, Hernández, & Castro, 2006;
Angelucci, 2008) and an increase in women’s reports that they
decide how to spend their own money (Attanasio & Lechene,
2002; Adato et al., 2000). A similar Brazilian survey
demonstrates
that Bolsa Família has a positive impact on women’s reports
that
they are the sole decision-makers in several areas of household
life,
including contraception and children’s school attendance, but
these results hold only among urban households (De Brauw
et al., 2014; also see Soares & Silva, 2010).4 Qualitative
researchers
find evidence linking CCTs to female control over family
expenses
(Streuli, 2012a; Morton, 2013; Adato et al., 2000; Adato &
Roopnaraine, 2010), men’s endorsement of women’s spending
power
(Maldonado, Nájera, & Segovia, 2006), and women’s expressed
sense
of autonomy (Rego & Pinzani, 2013; Suárez & Libardoni,
2007). The
qualitative research also documents extensive debates inside
house-
holds over which household member can rightfully claim a
share of
the CCT money (Pereira & Ribeiro, 2013; Corboz, 2013), and
researchers describe women’s efforts to divide CCT cash among

chil-
dren and spouses (Morton, 2015b, p. 1298; Pires, 2013; Ahlert,
2013;
for an overview, see Villatoro, 2005). In a critical vein, scholars
note
that CCTs may reinforce stereotypes about women’s obligation
to do
child-rearing labor (Gil-García, 2016; Mariana & Carloto,
2009). CCTs
may also impose time demands on women, increase women’s
work
(Molyneux, 2006; Molyneux, 2009) without asking for ‘‘greater
involvement by men” (Gomes, 2011, p. 78), and fail to create
space
for women’s public involvement (Gomes, 2011, p. 77; Suárez &
Libardoni, 2007, p. 126) or women’s participation in wage labor
(in
contrast to crèche programs; see Lavinas & Nicoll, 2006).
this puzzling result. Among small farmers at Rio Branco and
Maracujá, ‘‘shame”
(vergonha) is a highly prized virtue, a positive quality held to
be characteristic of the
countryside. People who exhibit ‘‘shame” are modest and
collaborate with others.
They are unlikely to report in a survey that they make decisions
fully by themselves.
However, not all small farmers successfully master the display
of shame. Those who
do not demonstrate appropriate shame may have difficulty
securing the approval of
welfare program administrators and complying with the
bureaucratic requirements
necessary to obtain Bolsa Família and maintain the benefit over
time. In rural areas,
then, the refusal to report independent decision-making may be
correlated with

‘‘shame” and hence with an increased likelihood of receiving
Bolsa Família.
354 G.D. Morton /World Development 113 (2019) 352–367
The gender lens has not been yet been focused on CCTs and
women’s asset ownership.5 Although evidence suggests that
CCTs
can increase household ownership of productive assets (Gertler,
Martinez, & Rubio-Codina, 2012)6, little research has been
conducted
on how CCTs affect the gendering of these assets inside the
house-
hold. Beyond the context of CCTs, however, a substantial
literature
considers the gender gap in assets and wealth. Scholars have
demon-
strated female disadvantage in the ownership of varied assets
(Doss
et al., 2014; Deere, 2010; Moser, 2010a; Antonopoulos and
Floro,
2005), particularly land (Agarwal, 1994; Deere and León,
2003).
Asset ownership has been shown to have profound implications
for women’s health, longevity, and resilience in crisis (Deere
and
Doss, 2006). Women’s asset ownership at the time of marriage,
in
some contexts, is associated with variations in the amount that
the
household spends on food, education, alcohol, and tobacco
(Quisumbing & Maluccio, 2003) and with women’s expectations
about household power (Fafchamps & Quisumbing, 2002;
Anderson & Eswaran, 2009). A policy granting assets to women
rather than men can lead to changes in household consumption

and spouses’ time allocation (Wang, 2014). The gender asset
gap,
however, does not look the same in every context; its size varies
across nations and across income groups inside nations (Doss
et al., 2014), depending on labor market conditions, legal
frame-
works, and social norms. Hence the literature includes repeated
calls
for attention to the institutions and practices that determine
owner-
ship at the local level (Deere, 2010; Deere & Doss, 2006;
Moser,
2010b).
Research in this area often intersects with scholarship on the
‘‘asset approach to poverty:” the effort to redefine poverty not
as
a lack of income, but as a lack of assets (Sherraden, 1988;
Sherraden, 1991; Sherraden, 2005; Bailey, 2010; Ssewamala,
Sperber, Zimmerman, & Karimli, 2010; Cramer & Shanks,
2014;
Moser, 2008). Researchers in this area emphasize that assets
have
a transformative effect on long-term life plans in contexts of
impoverishment (Moser, 2010a) and conclude that ‘‘the
accumula-
tion of assets might ultimately be more important for household
wellbeing than pure income measures” (Moser, 2010b, p. 394).
In
its focus on the difficult conversion between short-term income
and long-term assets, this literature overlaps with
anthropological
insights about money. Anthropologists have often observed the
creation of cultural systems that distinguish between the realm
of transient gain and the realm of enduring social reproduction
(Parry & Bloch, 1989, Introduction; Bohannan & Bohannan,

1968),
the latter sometimes being associated with constructed signs of
femininity (Taussig, 1980; Weiner, 1976).
The present article investigates households by considering con-
ditional cash, asset ownership, and gender dynamics in two vil-
lages in northeastern Brazil. The results are ethnographically
specific to a single time and place, but they point toward more
gen-
eral processes. The article argues that positive budget
disruptions
can help households overcome the gender asset gap, and the
article
5 There are some exceptions. For data that demonstrate that
women use Progresa
CCT payments to purchase small livestock, see Rubalcava,
Teruel, & Thomas, 2009. For
evidence that women are more likely than men to invest
Progresa CCT payments in
business and agriculture ventures, see Davis, Handa, Stampini,
& Winters, 2002.
Neither of these articles, however, provides new data to answer
the question of which
family member, inside the household, is considered to be the
owner of a given asset.
For an analysis of a Zambian unconditional cash transfer
associated with a sizable
increase in women’s asset acquisition, see Natali, Handa,
Peterman, Seidenfeld, &
Tembo, 2016.
6 For contrary evidence, see Maluccio, 2010; for a review, see
Kabeer, Piza, & Taylor,
2012, p. 24.
notes the usefulness of lump sums as a tool for creating such
dis-

ruption. After the introduction, Section 2 describes methods.
Sec-
tion 3 details the ownership of assets by gender at the field site,
and Sections 4 and 5 consider the effects of Bolsa Família and
the
Maternity Wage on ownership. Section 6 examines the gifts that
women give with Maternity Wage money. Section 7 discusses
the intra-household processes that underlie the effects observed,
and a final section concludes.
2. Methods
This article is drawn from a fieldwork project designed to
explore the expansion of Brazil’s rural welfare state under the
Workers’ Party. Fieldwork was conducted between 2005 and
2016 in the rural area of Vitória da Conqusita, Bahia, Brazil.
Core
activities took place in 2011–2013. Vitória da Conquista was
headed by a Workers’ Party mayor from 1997 to 2017, making
the municipality an apt site for the study of 21st-century
welfare
policy.7
Fieldwork was primarily based in two neighboring villages, here
called ‘‘Maracujá” and ‘‘Rio Branco.” The villages sit along
dirt
roads, about 100 km from the urban center. Both villages are
com-
posed of small farmers who rely on rainfall to raise livestock
and
cultivate dryland crops like beans, coffee, and manioc, with few
opportunities for regular waged employment. Rio Branco’s 103
inhabitants,8 living in 35 households, mostly belong to an
extended
family that has farmed the area since the 19th century.
Maracujá, by
contrast, has 205 inhabitants in 62 households. Maracujá village

was
founded in 1996, when landless farmers occupied a plantation
by
organizing themselves through Brazil’s Movement of Landless
Rural
Workers, the MST.9 The occupation was successful: the federal
land
reform agency expropriated the plantation, compensated its
owner,
and redistributed the land. Today, at Rio Branco and Maracujá,
almost all households have access to a plot of farmland.
Research was grounded in participant observation, including
interviews (Epstein, 1967; Briggs, 1986; Smith, 2014; Hardesty,
2015). I resided in the villages, living mostly in two families’
house-
holds. I accompanied people as they carried out their everyday
activities: work in the home, work in the fields, hospitable
visits
to friends, parties on the front porch, and appointments at the
wel-
fare office.10
Along with participant observation, I carried out a standardized
census with every household (96 total households)11 between
late
2011 and early 2012. Modeled on the PNAD,12 the census
asked
about each household’s earnings and assets for 2011; it also
inquired
into social program utilization and posed open-ended questions
7 For details on the sweeping changes that the Workers’ Party
has brought to
Brazil’s welfare state since the presidential elections of 2002,
see (Rego & Pinzani,
2013; Ansell, 2014).

8 Unless otherwise specified, all demographics for the villages
are for October 2011.
9 For more on Brazil’s landless movement, see (Morissawa,
2001; Loera, 2010;
Wolford, 2010).
10 All participants provided informed consent. The consent
process was approved as
IRB protocol H07130, University of Chicago.
11 In one household, the respondent declined to participate. All
other households
participated. One household reported a large negative income
for the year because of
the purchase of a number of cattle; I exclude this household
when reporting
information on income in the villages. The excluded household
did not receive either
the Maternity Wage or Bolsa Família. For details on the
exclusion, see (Morton, 2015a,
p. 454). In reporting currency from the survey, I use the
exchange rate of 1.86
Brazilian reais to 1 US dollar, the market rate for January 1st,
2012.
12 The Pesquisa Nacional por Amostra de Domicílios (PNAD)
is an annual household
survey conducted by IBGE, Brazil’s statistical service.
about work history, migration, and visions of the future.13 The
sur-
vey’s asset module included a checklist of moveable assets,
which
was written with the advice of village leaders.14 Houses and

land
were not included in the survey, since they were rarely bought
and sold in the villages. To assign a market value to the assets
on
the checklist, I spoke with knowledgeable merchants selling
compa-
rable items in the nearby city.
Based on the results of the census, I selected nine households to
participate in ‘‘focus family interviews.” I returned to these
same
households each week and asked about income and expenditures
for the week.15
Interviews and field notes provided the base for analysis. I
made
use of the recursive process characteristic of ethnography,
review-
ing results and refining hypotheses, then having subsequent
con-
versations in the field to check conclusions (Thorne, 2000;
Smith,
2014, p. 419). This checking confirmed that I needed more
infor-
mation about the Maternity Wage. Thus, I carried out a new
research stage in which I interviewed every woman who had
ever
been likely eligible for the Maternity Wage.16 After iterative
rounds
of checking, I presented results to local leaders, municipal
officials,
and social movement organizers. I also consulted with
specialists
on social assistance in the US and Brazil. These overlapping
sources
made it possible to search for alternative interpretations,

thereby
helping to test conclusions.
3. Ownership, assets, and gender in the villages
Small-farming families have to contend with a dry landscape at
Maracujá and Rio Branco. Families reside in small houses,
usually
whitewashed, and in order to facilitate water delivery these
homes
are clustered together near the dirt soccer fields and the
Protestant
and Catholic chapels that form the center of each village. With
rare
13 The survey was conducted by me directly. I lived in the
villages and had personal
relationships with village residents, which might have
influenced responses. In some
cases, respondents might have attempted to deceive me for
personal reasons. In other
cases, they may have been more honest about their asset
ownership, knowing that I
could potentially see assets for myself. Residence in the
villages also made it easier for
me to determine how long each person had been living in the
countryside, which was
an important element in determining eligibility for the
Maternity Wage. I became
familiar with the reasons behind the gap between actual
residence and proof of
residence, a gap that lies at the root of many problems in
obtaining the Maternity
Wage.
14 The module also asked respondents to identify any other
objects of value that
they owned. On the standard checklist, respondents were asked
about the number of

the following items that they owned: cows, pigs, chickens, bee
hives, guinea fowl,
horses, donkeys, mules, sheep, ducks, goats, turkey, other
animals, tables, chairs,
stoves (wood or gas), computers, refrigerators, horse-drawn
carts, cars, pots and pans,
bicycles, motorcycles, beds, televisions, radios, CD players,
DVD players, telephones
(land line or cell), phone antennas, water filters, water tanks,
parabolic TV antennas,
freezers, clothes washing machines, sofas, kitchen shelves,
clothes wardrobes, living-
room shelves, television shelves, chests of drawers, fans,
sewing machines, electric
shower heads, clothes irons, rugs, video games, cameras, water
pumps, and guitars.
The checklist did not include clothes, jewelry, or shoes, because
of the difficulty of
enumerating separate small items and also because informants
reported that these
items were not significant stores of wealth in the local area.
15 The focus family interviews continued for a period ranging
from two to six
months, depending on the household. For details on the methods
used in all of these
surveys and the survey results, see Appendix 1 from (Morton,
2015a).
16 The new stage identified 24 women who had applied for the
Maternity Wage, of
whom 12 received the benefit. This is a small group on which to
base an analysis.
Fortunately, however, the Maternity Wage was a major topic of
conversation among
many people living in the villages at the field site, so I was able
to compare the
opinions and practices of actual Maternity Wage recipients with

the viewpoints
expressed by a larger number of village residents. In total, I
interviewed 49 women
who were likely eligible for the benefit (see Table 2), and I had
informal conversations
about the Maternity Wage with a much more diverse group of
women and men. I
found the views of non-recipients to be highly consistent with
the practices of
recipients. There was widespread agreement that, if a woman
received the Maternity
Wage, she should spend it on a productive agricultural asset.
This consistency
provided some reassurance that the behavior observed among
the small group of
recipients was behavior that corresponded to a widespread norm
at the field site.
exceptions, no irrigation is available. Farmers count on the
region’s
twice-annual rains to grow coffee, manioc, and pineapples for
mar-
ket sale or home consumption, with beans, corn, dryland sugar
cane and garden vegetables grown for home consumption only.
Farmers also raise livestock, particularly cattle, pigs, and
chickens.
Typical family farms range in size from ten to twenty hectares.
Given the arid climate and the distance from an urban market,
most families cannot subsist on farming alone. They combine
income from a variety of sources, including retirement
pensions,
employment in rural schools and health clinics, day labor on
nearby plantations, and cyclical migration to cities or more
distant
plantations. In the 2011 survey conducted as part of this
research,

median annual household income (excluding Bolsa Família and
Materntiy Wage) for the two villages was R$2732 (US$1469)
per
capita.
People at Maracuá and Rio Branco tend to live in households
anchored by a male-female couple, often with their children,
grandchildren, in-laws, siblings, or friends residing in the home
as well.17 Each adult will usually contribute to the household’s
sus-
tenance through several forms of work.18 In the dominant local
model, women specialize in housework, child care, and the
home
production of food for sale, while men devote themselves to
work
in fields. But gender stereotypes about work are not
unbreakable.
Women toil in rows of plantation coffee, team up with friends
to
plant their own bean fields, and travel to the city so they can
labor
in factories. Men watch children and teach classes at school.
Because of the arid climate, farmers cannot count on crops
every year. It becomes especially important to hold assets,
partic-
ularly livestock, that can be sold in a time of need. Beyond
animals,
households own a range of other moveable assets, including
furni-
ture, appliances, and motorcycles. In 2011–2, the average
house-
hold in Maracujá owned moveable assets (including livestock)
valued at 2.69 years’ worth of the household’s annual income;
in
Rio Branco, 1.55 years’ worth of annual income. In each

village,
livestock accounted for nearly half of the value of these assets.
(Insert Figs. 1 and 2 here.)
Livestock, however, do not usually belong to a household. They
belong to a particular person inside the household. In everyday
social interaction between villagers, intra-household ownership
becomes perhaps most salient through the practice of gift-
giving.
It is common for adults to give livestock as a gift to children.
The
act of gifting requires an adult to declare that he or she owns an
animal and then transfer ownership publicly to the child. These
declarations become the topic of neighborly conversation, with
farmers spreading the news of a gift. Thus, which animal
belongs
to which household member is common knowledge. Neighbors
remember that the black spotted cow belongs to the oldest
daugh-
ter in the family next door, or that the duck wandering through
the
backyard is the property of the younger son.
Beyond the case of livestock gifts, however, it is frequently
con-
sidered contrary to the ethos of cooperation for a person to
declare
that certain objects in the household belong to herself or
himself
individually. Respondents explained to me that naming
individual
owners of assets is a sign of family discord. This leads to
difficulties
in interpreting survey responses. Interviewees often expressed
ambivalence about which person inside the household was the
owner of which assets. Some respondents identified more than

17 More than half of households have children living in them,
and more than 75% of
these households with children have a male-female couple
living in them (not always
the child’s parents). For details, see (Morton, 2013) footnote 4
and (Morton, 2015a),
Appendix 1.
18 Child labor is now rare in the villages, beyond chores at
home and occasional help
in the family fields. However, villagers report that child labor
was common on
plantations and in small fields as recently as ten years ago.
Villagers say that child
labor has stopped because of rigorous government enforcement
of laws, along with
the recent appearance of schools and social programs in the
countryside.
Fig. 1. Household income and moveable assets, per capita, Rio
Branco.
Fig. 2. Household income and moveable assets, per capita,
Maracujá.
356 G.D. Morton /World Development 113 (2019) 352–367
one owner for an object—as in the case of a male farmer who
told
me that the cattle belonged to him, although he considered that
they also belonged to his wife.
But while respondents express reticence about claiming objects
for themselves, there exist patterns in the responses. These pat-
terns emerge when one considers the person whom a respondent
first mentions in connection with an object. Men are

overwhelm-
ingly, but not exclusively, described first as the owners of
cattle.
Villagers speak of senior men as the owners of the houses, since
it is believed to be the man’s duty to build a house. Although it
is not habitual to describe any individual as the owner of crops
in the field, men are closely associated with cash crops, because
Table 1
Access to benefits, Maracujá and Rio Branco, 2012.
Number of households. . . Maracujá
62
households,
205 people
Rio Branco
35
households,
103 people
Total for
both
villages
Receiving BF 31 20 51
Not receiving, but likely
eligible
8 2 10
% of likely-eligible households
that receive BF

79.5 90.9 83.6
Have received Maternity
Wage
6 6 12
Did not receive, but likely
eligible
25 12 37
% of likely-eligible households
that receive Maternity
Wage
19.4 33.3 24.5
Data from census conducted by author in two villages, 2011–
2012.
men often work in the fields, sell the crops, and pocket the
money.19 On the other hand, in interviews, senior women tend
to
be mentioned first as owners of domestic objects—stoves, beds,
linens, and plates, some of which may have come in the bride’s
trousseau. This distinction between male objects and female
objects
corresponds to the (loosely-enforced) local model in which men
in
the villages work outside the house and women work inside of
it.
As two women explained it to me in conversation one day, the
man owns the house, but the woman owns everything inside it.

In the household, then, both men and women possess assets
that hold value over the long term. These assets hold value for
dif-
ferent reasons, however. Women’s objects hold value because
they
are durable, and these objects become more influential as they
become more durable. A better stove will last longer and hence
extend the influence of the woman who owns it. By contrast,
men’s
objects, in at least some cases, hold value because they are
repro-
ducible. A cow gives birth to more cows, stretching value
forward
across generations. Crops are harvested and the seed is sown
again.
As men’s assets reproduce, they also produce income. Some
calves
can be slaughtered; some of the harvest can be sold. While
women’s objects slowly lose value over time, men’s objects
may
hold value steady or, through the reinvestment of income in the
field or herd, even increase in value (see Weiner, 1976, p. 236).
This is the pattern of asset gendering that Bolsa Família tends
to
reinforce in the villages. The Maternity Wage, however, can
disrupt
the pattern. The following sections describe the two programs’
impact on asset ownership inside households.
4. Bolsa Família and asset purchases
In 2011–12, Bolsa Família was widespread in the villages; 84%
of likely-eligible households were receiving the benefit.20 In
the
51 receiving households, Bolsa Família payments ranged from

R$
38 (US$ 20) to R$ 226 (US$ 122) per household per month,
with a
mean payment of R$ 117 (US$ 63) (SD = 42.7, median = 102).
(Insert
Table 1 here.)
Bolsa Família benefits are delivered on a monthly basis, and the
money is often spent on fast-cycling items like food and school
supplies. However, women report in interviews that they also
strive to set aside at least a portion of the Bolsa Família cash
each
month so they can turn it into a durable asset.
They can achieve this thanks to roving peddlers called mas-
cates.21 The peddlers play a major role in the use of Bolsa
Família
in the countryside. Mascates ply the back roads in heavily-laden
cars
and small trucks, passing through each village once a month.
They
sell furniture, appliances, and other household items. Villagers
report that Bolsa Família has allowed mascates to extend their
reach
into rural areas. Aware that his22 customers now have a source
of
monthly income, a mascate provides credit on a personal basis.
He
delivers a stove, couch, or similar item to a family as soon as
the fam-
ily makes the first payment, then he returns each month to
collect
installments until the debt is paid. Although the poorest women
have difficulty devoting any Bolsa Família money to assets
(Morton, 2013), mascates facilitate purchase by offering
flexible

and renegotiable terms of credit. In exchange for credit and
conve-
nient transportation, mascates charge prices much higher than in
19 Women do sometimes plant crops by themselves or in
conjunction with other
women, but these are typically subsistence rather than cash
crops.
20 I determined likely eligibility for Bolsa Família and the
Maternity Wage by taking
the information that each household reported to me on the
census survey and
comparing that information to the government’s eligibility
requirements for the
programs. When necessary, I also considered further
information from the household,
such as length of residence in the countryside.
21 The name mascate comes from the city of Muscat, in Oman,
which since ancient
times has served as a commercial emporium.
22 At Maracujá and Rio Branco, mascates are overwhelmingly
men.
the city—typically double, according to a merchant I
interviewed in
2012. Despite prices, the mascate system has led to a rural
expansion
in durable goods, from metal pots and blenders to couches and
televisions.
Women plan these purchases well in advance. They often speak
about the objects they aim to acquire with Bolsa Família:
perhaps a
bed for a child, then, once it is paid off, a couch, then a
television.
Dona Marlene recalled the history of the items she had bought,
one
after the other, in a chain of installment payments stretching

over
years.
23
‘‘a
no
m
ac
m
Right now just recently I
bought this stove with the
Bolsa Família money. [. . .] I
bought a sieve [. . .] I
bought the ceramic tiles for
this house. I made a
monthly credit agreement
for fifty reais. So I would
pay the fifty reais for the
credit payment on the tiles.
Then, after I finished the
tiles of this kitchen – [. . .]
Then I bought – that
kitchen cabinet there, look
at it.
From an anthropological perspective,
ccounting models” rather than ‘‘mental
t, in fact, the minds of my interlocutor
odels) of their action and the reasons beh
counting” is well established in the lite
ental accounting, see Thaler, 1990 and K
Agora mesmo esses dias eu
comprei esse fogão com o
dinheiro da Bolsa Família.
[. . .] Eu comprei peneira. [. . .]
Eu comprei a cerâmica dessa
casa. Aí eu fiz uma prestação

de cinquenta reais. Aí eu
pagava os cinquenta reais da
prestação da cerâmica. Aí,
depois que eu terminei a
cerâmica dessa cozinha—[. . .]
Aí eu comprei-- esse armário
aí, Ó.
In the villages, some Bosla Família beneficiaries describe a
charac-
teristic ‘‘mental accounting” practice that they follow in order
to
budget the benefit money.23 First they decide on an amount
they
can devote to assets each month. Then they commit to credit
with
a mascate (or sometimes a store) for this amount. Finally, after
the
monthly asset money has been spent, the remaining money is
avail-
able to buy transitory items, like food.
Martina used this practice to spend fifty reais per month on
household assets. Martina received a little more than R$100 in
Bolsa Família each month. She recounted the reasoning that she
used to allocate this money.
it might be preferable to speak about
accounting,” since what I observe here is
s, but rather their own descriptions (or
ind it. However, because the term ‘‘mental
rature, I follow common usage here. On
och & Nafziger, 2016.
2

Fa
fro
ot
Bu
els
th
in
sp
du
fie
th
ho
co
m
ad
fo
ab
re
sit
to
ex
an
–
hu
358 G.D. Morton /World Developm
Bolsa Família isn’t enough for
you to buy things, only if
you put together money
from several months, you
know? [. . .] I myself, I
always buy something like
that, something that costs
around fifty reais. Because
then you’ve got—I’m going
to make the monthly credit

payment, and I’ll have
another fifty left over. So I
always buy like that, on
credit, and I pay and pay.
Every month that I get
Bolsa Família, I go right
there and make the credit
payment.
4 It is especially striking that women ma
mília on durables rather than food, sinc
m cash transfer programs in other nation
her nations, see Adato et al., 2000, p. xi
dgeting practices in northeastern Braz
ewhere because of specific expectation
at men should take on the responsibility o
the poorest households at Maracujá and
end all of the benefit money on food,
rables; see a longer discussion in (Morto
ld site mentioned the following worry, i
at men might contribute less money to
usehold received Bolsa Família or the Ma
uld conceivably ‘‘crowd out” men’s spend
embers of the household. This concern m
amant views about the importance of no
od, which was the man’s paradigmatic r
out the changes in men’s spending patte
ceive benefits. However, it is worth notin
e and elsewhere, suggests that Bolsa Fam
devote increased resources to self-empl
ample, in one household that I accompan
d a husband both told me with great enth
how Bolsa Família covered some basic
sband to devote time to improving the f
A Bolsa Família não dá para
você comprar, só se você for
juntando várias meses, né?

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