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Together We Will: Experimental Evidence on Female

Voting Behavior in Pakistan

Xavier Gin and Ghazala Mansuri

This version: July 2012

are more likely to follow the wishes of male household and clan heads.We assess the impact of a
voter awareness campaign on female turnout, candidate choice and party vote shares. Geographic
clusters, some households were left untreated. Compared to women in control clusters, both
Data from polling stations suggests that treating 10 women increased female turnout by about 9

JEL: D72, P16, 012
Keyword: externalities, spillovers, information campaign, voting behavior, elections, field

Gin: Development Research Group, The World Bank ( Mansuri: Development
Research Group, The World Bank (e-mail: We thank Abhijit Banerjee, Marco Castillo,
Rachel Croson, Jishnu Das, Quy-Toan Do, Marcel Fafchamps, Haris Gazdar, Donald Green, Alan Gerber, Dan
Houser, Macartan Humphreys, Raquel Fernandez, Shareen Joshi, Stuti Khemani, Betsy Levy-Paluck, Monica
Martnez-Bravo, Kevin McCabe, Berk Ozler, Ragan Petrie, Debraj Ray, Mark Rosenzweig, Jennifer Tobin and
Pedro Vicente for valuable discussions and advice. We are especially grateful to the following for their help and
support in organizing the experiment: Shahnaz Kapadia, at ECI Islamabad, for her help with designing and pilot
testing the information campaign; Irfan Ahmad at RCONs, Lahore, for managing all field operations and data
collection; Sughra and Ashiq Solangi of The Marvi Rural Development Organization, Sukkur, for their tremendous
support to the team throughout; Qazi Azmat Isa at the World Bank Office in Islamabad and Kamran Akbar at the
Pakistan Poverty Alleviation Program (PPAF) in Islamabad for their support and encouragement. This project was
jointly funded by the Development Research Group at the World Bank and the PPAF. Paloma Acevedo, Paola de
Baldomero, Jordi de la Torre and Santhosh Srinivasan provided outstanding research assistance. The views
expressed herein are those of the authors and should not be attributed to the World Bank, its executive directors, or
the countries they represent.
1. Introduction
A basic premise of representative democracy is that those who are subject to policy should have
a voice in its making. Although women account for half of the worlds population, they have
historically lagged behind men in legal and political rights. In recognition of this, suffrage was
extended to women in most western democracies in the early 20
century and the new
democracies that emerged after WWII followed suit and granted women de jure rights to
political participation in all democratic institutions.

Despite these improvements, women are still far less likely than men to stand for public office,
even in developed countries with older democracies. They are also less likely to participate in
the electoral process as voters or to exercise independence in candidate choice when they do
vote. Instead, women report voting in accordance with the preferences of the caste, clan or
household head in contrast to men of all ages (CLRAE, 2002).

While womens relative absence from elected public office has received considerable policy
attention in recent years
, there have been few attempts to reduce barriers to womens
participation as voters, and even less attention has been paid to the use of women as passive vote
banks, when they do participate. If preferences over the allocation of public resources vary by
gender, this neglect could have implications for public policy, in addition to equity related

These rights were also brought into international law by several important agreements to which most countries are
signatories. These include the Universal Declaration of Human Rights (1948), the Convention on the Political Rights
of Women (1952); the International Covenant on Civil and Political Rights (1966); and the Convention on the
Elimination of All Forms of Discrimination against Women (1979).
See also Zia and Bari (1999) and Bari (2005) for Pakistan.
A number of countries have passed legislation requiring fixed quotas for women. In South Asia, for example,
India, Pakistan and Bangladesh have all instituted quotas for women in both local and national assemblies.
Chattopadhyay and Duflo (2004) exploit the quota introduced for women in the Indian Gram Panchayats and find
that elected women leaders are more likely to provide public goods preferred by women. Lott and Kenny (1999) find
that womens suffrage in the US increased overall government revenues and expenditures and has led to more liberal
voting patterns. Edlund and Pande (2002) find that the decline in marriage has contributed to the shift by women
voters in the US towards the Democratic Party. Several studies of intra-household resource allocation (e.g. Thomas
(1990), Lundberg and Pollack (1997) and Hoddinott and Haddad (1995)) have also shown that women tend to make
different choices over the allocation of household budgets, such as higher investments in health and the education of
children. Croson and Gneezy (2009) review the experimental literature on gender differences in preferences related
to risk, social attitudes and competition.


Although many factors affect the decision to vote, women in emerging democracies may face in
particular two distinct barriers. First, costs of participation may be too high. Traditions or
cultural stereotypes may discourage the exercise of own preferences, mobility constraints may
limit participation and, if there are expectations of voter intimidation or violence, personal
security concerns may also loom larger among females. Second, women may have fewer or
process, perhaps due in part to illiteracy and limited mobility. Lack of information may also
reinforce stereotypes that further disengage women from public life. If lack of awareness limits
participation, as studies suggest, then access to information could enhance both equity and
allocative efficiency as women select candidates that best reflect their preferences. Moreover,
while attitudes and social mores tend to change slowly, the mere act of participation may serve to
weaken pejorative perceptions about female efficacy that limit womens engagement in public
life (Beaman et al., 2007, Bagues and Esteve-Volart, 2012, Mansuri and Rao, 2012).

Related, because voting involves a civic duty, it is likely that voting behavior is influenced by the
behavior of others, either because women obtain information from talking to other women
(Lazarsfeld, Berelson and Gaudet, 1944) or because voting is subject to peer pressure and social
norms (Riker and Ordeshook, 1968; Knack 1992 and Opp, 2001).
We test these ideas by conducting a field experiment to assess the impact of information and
social interactions on female turnout and independence of candidate choice. The setting for the
experiment is rural Pakistan where women still face significant barriers to effective political
participation, despite legislative reforms aimed at enhancing female participation in public life.
Zia and Bari (1999), for example, report that women are often not registered as voters because
lack knowledge about the electoral system and about voting.
The awareness campaign was conducted just before the 2008 national elections, after the voter
registration period had ended. Study villages were divided into geographical clusters which were
randomly assigned to treatment or control. Within treated clusters, only a subset of sample

A number of recent studies have looked at the role of geography, shifts in technology and the development of
institutions in the formation of cultural attitudes and beliefs about gender roles. See for e.g. Alesina et al (2010),
Alesina and Giuliano (2010), Fernandez (2007), Fernandez and Fogli (2009) and Fortin (2005).

households was randomly assigned to receive a door-to-door awareness campaign. This allows
us to assess social interactions within treated clusters without confronting the usual set of
identification problems (Manski, 1993; 1995).
The campaign was developed as a set of simple visual aids with two different messages: the
importance of voting which focused on the relationship between the electoral process and policy,
and the significance of secret balloting which explained the actual balloting process. Treated
women received either the first message or both messages, allowing us to test whether
knowledge about the voting process, including the fact that ballots are cast in an environment of
secrecy, enhances female participation and independence in candidate choice.
We find that turnout increases by about 12 percent for women in treated households compared to
women in control clusters, with somewhat larger and more precise effects for women exposed to
both messages. More importantly, we find comparable turnout rates for the untreated close
neighbors of treated women, indicating large geographical spillovers. We then assess whether
spillovers among close friends are larger than those among neighbors. The results are
qualitatively similar. This is not too surprising given that close friends typically reside nearby. In
addition, we use the GPS location of households to estimate spillovers beyond the (arbitrary)
boundaries of the treatment clusters and find even larger effects.
Given that about three clusters are mapped on average to a polling station, and that there are one
to three polling stations per village, we complement the sample data with administrative data
from all polling stations that served the study villages. We find that for every 10 treated women,
(roughly 4 households), female turnout increases by about 9 additional votes. Once we take this
externality into account, the cost of the intervention drops from US $16.7 to about US $2.2 per
additional vote. In contrast, using the same administrative data we find no effect on male turnout,
suggesting either that the provision of information on the electoral and balloting process is less
salient for men or that men are simply not influenced by information provided to women.

We turn next to whether the campaign influenced candidate and party choice. We find that it did.
Treated women are significantly more likely to vote for the second most voted political party.

One could also argue that there is little communication about political matters between men and women. The post
election survey refutes this view since about one half of women in the sample report frequently discussing political
issues with men in their households before the election.

Further, control women in treated clusters behave as if directly treated, confirming once more the
importance of social interactions. Polling station data show that an increase of 10 percent in the
share of treated women led to a decrease in the share of female votes for the winning party of 6
percent. These results suggest that the campaign could have influenced the share of votes at the
constituency level and thus the policy agenda, had it been implemented at a larger scale
(Fujiwara, 2011).
Given this result, we next check whether treatment decreases the male heads knowledge of the
candidate choice of women in his household. Follow-up survey data asked the male head and
each woman in the household about whether other women in the household had cast a vote and
for whom they had voted. Using these data we construct cross-reports regarding candidate
choice. We find that male heads in treated clusters are indeed significantly less informed about
the candidate choice of women in their households.
Interestingly, we also find evidence of cognitive dissonance (e.g., Mullainathan and Washington,
2009). Women in the randomly assigned control clusters, among whom turnout was lower, were
more likely to report witnessing or hearing instances of violence in the village, compared to
reports by women in treated clusters.
This paper therefore contributes to two literatures. First, it adds to the nascent literature on pre-
election voter information campaigns in developing countries. Second, it contributes to the
burgeoning literature on social networks and peer effects (see, for example, Kremer and Miguel,
2001; Duflo and Saez, 2003; Kling, Liebman and Katz, 2007 and Bobonis and Finan, 2009).
While there is an extensive literature on the impact of Get-out the Vote or GOTV campaigns in
developed countries, and in the US in particular (see Gerber and Green, 2000a and 2000b), much
less is known about the impact of such campaigns in developing countries where voters tend to
have poorer access to information, institutionalized party structures are less developed and voters
are often engaged in clientelist relationships that influence voting decisions (see Aker et al. 2011,
Banerjee et al. 2011 and Guan and Green 2006; see Pande 2011 for a review).

In developing countries there is a small experimental literature that has focused on electoral violence, clientelism
and vote buying. Collier and Vicente (2007), for example, study the effect of an information campaign on electoral
violence in Nigeria. Wantchekon (2003) has examined the effectiveness of clientelist messages in Benin and Vicente

Because female mobility is restricted, social networks among close neighbors are likely to play
an important role in the diffusion of information. To our knowledge, this is one of the first papers
to systematically assess the impact of information externalities on voter turnout and candidate
and party choice.
Understanding the scope for such spillovers is important for measuring the
cost-effectiveness of an information campaign and for assessing the types of information that can
be successfully transmitted through social networks.
Indeed, we provide evidence suggesting that the information content of the campaign did matter.
Control women in treated clusters are far more likely than women in control clusters to discuss
political issues with their neighbors, including political party and candidate positions and the
importance of voting in accordance with ones own preferences. Moreover, even the more
nuanced message about the secrecy of the ballot played a role because male heads of control
households in clusters treated with both messages were significantly less informed about the
candidates chosen by women in their household, compared to male heads in control households
in clusters only treated with the message about the importance of voting.
We conclude that while peer pressure may have contributed to the increase in turnout (Funk,
2010), the impact of the campaign on party shares indicates a direct effect of its informational

(2007) analyzes the impact of an information campaign on vote buying in Sao Tome and Principe, Vicente and
Wantchekon (2009) provides a review.
In an experiment in the US where voters received postcards with information about their voting record, Gerber et
al. (2008) find that turnout increased by about 8 percent in households that were shown their voting records as well
as that of their neighbors. This increase in turnout is comparable to the impact of direct canvassing. Our paper is
perhaps closest, in spirit, to Nickerson (2008), which assesses information spillovers within the household. The
paper reports on a door-to-door canvassing experiment, which targeted households with two registered voters. The
author finds that the member that did not answer the door is nearly 60% as likely to vote as the directly treated
member. In contrast, Nahomi (2011) looks at the spillover effects of domestic observers on voter registration and
turnout in non-monitored polling stations in Ghana, and Guan and Green (2006), designed their experiment to limit
the spillover effects of a GOTV information campaign conducted in China.
While the objective of the campaign was to provide information rather than to persuade women to vote, we cannot
rule out that it did. One could also argue that the increase in turnout was due to the salience of the campaign (e.g.
Zwane et al. 2011). However, at the time of the visit, households were already subject to multiple stimuli to vote.
Indeed, over 75 percent of them reported receiving a visit prior to the election from party volunteers asking for their
vote. Alternatively, one could argue that the visit itself could have motivated treated women to vote (if they felt
special for having been chosen and voted out of reciprocity), but this is unlikely because untreated women in treated
clusters (not chosen to receive the visit) show turnout rates that are comparable to those of directly treated women.

The remainder of the paper is organized as follows. Section 2 describes the context of the 2008
election, the design of our experiment and the data. Section 3 describes the empirical strategy
and results. In particular, Section 3.1 discusses the impact of the information campaign on
turnout and assesses the size and significance of information spillovers, Section 3.2 discusses the
evidence on independence of candidate choice, Section 3.3 examines the interaction between
electoral competition and information provision and Section 3.4 assesses the impact of the
campaign on knowledge and perceptions. Section 4 provides a cost-benefit analysis of the
intervention and Section 5 concludes.
2. Context and Experiment Design
The experiment was carried out in collaboration with the Pakistan Poverty Alleviation Fund
(PPAF), the Marvi Rural Development Organization (MRDO), Research Consultants (RCons),
ECI and the World Bank. PPAF is an apex institution created in 2000 with World Bank funding.
PPAF provides capacity building and funding for community based development and
microfinance to its partner organizations which are mostly NGOs. MRDO, a non-partisan
organization that works with rural women, is one such NGO. RCons, a survey firm, helped
MRDO implement the awareness campaign and collected the baseline and follow-up data. ECI, a
non-partisan local training firm, collaborated in the design of the campaign. ECI had prior
experience with the development of visual aids and pamphlets related to electoral participation
and the balloting process. It was also actively engaged in the training of local election officers
nationwide prior to the elections.
2.1 Context
The campaign was carried out in the districts of Sukkur and Khairpur in the southern province of
The districts were selected because of sharp electoral competition between the two main
political parties, the Pakistan Peoples Party Parliamentarians (PPPP), which has a secular-left
leaning platform and the Pakistan Muslim League Functional (PMLF), which was allied with the
military regime.

The population of Sukkur is estimated at 650,000 (2011) while that of Khairpur at about 130,000 (2006)

The initial sample included 12 villages, 6 from each district, and 24 polling stations from two
All candidates from both parties in these two constituencies were male.
Villages were chosen to ensure variation in expected political competition at the polling station
level, but given the context of the 2008 elections, 3 villages (3 polling stations) had to be
dropped because the safety of the canvassing teams could not be guaranteed. The polling stations
in these 3 villages were relatively more contested than those in our final sample of 9 villages and
21 polling stations. According to Panel A of Table 1, these 21 polling stations had an average of
434 registered women. In the sample, we have 89 treated women per polling station, on average.
In Section 3 we exploit the random variation in the percentage of treated women per polling
station (ranging from 8 to 66 percent) to assess the impact of treatment on turnout and the share
of PPPP among female voters.
Indeed, the 2008 national elections were held in an environment that was politically charged.
After seven years of military rule, culminating in widespread opposition, the government
declared emergency rule. The sitting judges of the Supreme Court were dismissed and there were
fears that the incumbent government would engage in massive rigging. Scheduled initially for
January 8
, 2008, the elections were postponed to February 18
, 2008 because Benazir Bhutto,
the leader of the PPPP, and a twice-elected Prime Minister, was assassinated on December 27
In Sindh, traditionally a PPPP stronghold, a large turnout and a PPPP landslide was being
anticipated due to a possible sympathy vote for Bhutto. At the same time, the expected PPPP
landslide could have served to discourage supporters of PML-F, depressing turnout. Finally,
there were concerns about electoral rigging and voter intimidation by the incumbent military
government, though these decreased after Bhuttos assassination and the increased visibility of

The average size of a village in Sindh is just under 300 households, though villages can be as small as 80
households and as large as 1500 households. Study villages are close to the average with roughly 350 households
per village.
Twelve polling stations were from the National Assembly constituency NA-199 (Sukkur) and the remaining 12
from NA-215 (Khairpur). NA-199 had a total of 242 polling stations while NA-215 had 270 polling stations. The
same 12 polling stations belonged to Provincial Assembly constituencies PS-4 (Sukkur) and PS-32 (Khairpur),
respectively. PS-4 had 125 polling stations in total and PS-32 had 114. Sukkur and Shikarpur districts have 2
National Assembly constituencies (NA-198 and NA-199), while Khairpur has 3 constituencies (NA-215, NA-216
and NA-217). There are 4 Provincial Assembly constituencies in Sukkur and Shikarpur (PS-1 to PS-4) and 6 in
Khairpur district (PS-29 to PS-34). See for more information.

the elections. The net effect of these tendencies on turnout and party choice, particularly for
women, was uncertain.
The campaign was delivered door-to-door by a team of two women and was only attended by the
women in each household. No men were allowed to be present during the sessions.
It was
designed as a set of simple visual aids accompanied by a well-rehearsed and limited script. The
campaign included two nonpartisan messages: the first focused on the importance of voting, the
relationship between the electoral process and policy, including village development outcomes,
while the second focused on the actual balloting process, including the structure of a typical
voting station and booth, the fact that male and female booths are separate, the secrecy of the
ballot and the basic appearance of the ballot paper.
Since the objective of the second treatment
was to inform women about the balloting process as a whole, we cannot separately identify the
impact of ballot secrecy, from other aspects of the process. The information campaign never
mentioned a political party or candidate by name.
It is worthwhile stressing that unlike most
GOTV campaigns, whose main objective is to increase turnout by persuading subjects to vote,
the objective of the voter awareness campaign was to inform women about their rights in the
electoral process and how to exercise them.

Appendix A contains the translation of the script and
Appendix B the translated visual aids.
The campaign was implemented door-to-door for two main reasons. First, it provided a high
degree of control over which households received the campaign and which did not, which was

In many cases, men were not at home at the time of the visit, which took place during the morning and early
afternoon. If men were home, they were requested to allow the female team members to meet with the women alone.
In most cases this did not pose a problem since men are not usually present in an all womens gathering. In the few
cases where men were reluctant to leave, the male supervisor discussed the information campaign in general terms
with them and obtained agreement.
Even in developed democracies where ballot secrecy is perfectly enforced, Gerber et al. (forthcoming) find that a
significant fraction of respondents in a nationally representative survey in the US do not believe that their ballot
choices are kept secret.
A GOTV campaign can be partisan or not, though a number of experimental studies have shown that partisan
messages are less successful in motivating turnout. Cardy (2005), for example, finds that neither partisan direct mail
nor partisan phone calls - used independently or together - managed to garner a significant voter response. In a
similar vein, Gerber and Green (2000b) find that non-partisan messages are particularly effective in mobilizing
unaffiliated past voters. The authors hypothesize that partisan voters may already receive adequate encouragement
from their respective political parties while unaffiliated voters do not. Moreover, they speculate that politically
unattached voters may also have been impressed by the non-partisan appeal to civic responsibility. Horiuchi et al.
(2007) also find that voters are less likely to abstain when they receive policy information about both ruling and
opposition parties through their official party websites. The information effects are larger among those voters who
were planning to vote, but were undecided about which party to vote for.

critical for measuring information spillovers as well as the cost-effectiveness of the intervention.
Second, door-to-door information campaigns in the US have been more effective in inducing
turnout than other strategies like phone calls and direct mailings.
In our context, door-to-door
visits were also the most feasible choice given the low levels of literacy and cell-phone
ownership among women, combined with low female mobility.

Table 1 Panel C indicates that female literacy rates are indeed very low in our study area, as they
are all over rural Sindh. Less than 20 percent of adult women have any formal schooling.
Women also have limited mobility even within their own villages. Most women in our sample
can travel within the village on their own or accompanied by other females but not outside the
village, where the presence of a male is required.
Appendix Table A2 presents gender differences in access to media, knowledge of current events
and participation in public life. The sample is confined to comparisons between the male head
and his spouse. Women are far less likely to listen to local, national or international news
channels (10 percent of women report listening to BBC compared to 48 percent of men, for
example) and are far less informed about any political issue, including major events like the
imposition of emergency rule in the country, which only 6 percent of women knew about, as
compared to 82 percent of men. Women are also less likely to be able to correctly identify
political party signs and names. Interestingly, this difference is not due to differential access to
TV or radio. Instead it appears that men and women use media very differently.
Women are
also less engaged with any aspect of village public life. They are far less likely, for example, to
attend community meetings related to village development, attend demonstrations or contact
their local councilor or local party official for any matter. Interestingly, though, when they do

Gerber and Green (2000a) report on a randomized GOTV campaign conducted in New Haven, Connecticut, just
prior to the 1998 election. The campaign delivered non-partisan messages through personal canvassing, direct
mailings and telephone calls. The study found that personal canvassing had a substantially greater impact on voter
turnout as compared with other modes of contact. Green et al., (2003) and Michelson (2003) find similar results.
See Jacoby and Mansuri (2011).
Table A2 indicates that both radio and TV are widely available and that if anything, women report higher access
than men. Approximately, 42 percent of men and 47 percent of women had access to a radio and about 65 percent of
men and 67 percent of women had access to a TV.

engage, women tend to avoid formal authority and reach out to traditional or religious leaders
(66 percent among women compared to 49 among men).

2.2 Experimental Design and Data
The timeline of the study is shown in Figure 1. The information campaign was deliberately
carried out after the voter registration period had ended, two weeks prior to the elections (from
February 5
to 15
2008). Each sample village was covered in approximately one day. The
campaign was implemented by 8 teams, which consisted of one MRDO female staff member,
and one female enumerator, from RCONs.
Each village was completely divided into
geographical clusters, consisting of one or two contiguous streets, with about 40 households per
cluster, on average. A cluster always fell inside the catchment area of a polling station. This
yielded one to nine clusters per polling station, with an average of 3.2 clusters, of which zero to
seven clusters were treated, yielding an average of 2.7 treated clusters per polling station.
Clusters were based on geography because social interactions are mostly dictated by physical
proximity given the restrictions to female mobility. Each cluster was then randomly assigned to
receive the importance of voting message (T
), or T
plus the voting process message (T
) or
nothing. The canvassing team selected one cluster in each village at random and began there. T

was delivered in this cluster. Moving from this point, every other cluster was selected for the
study, thereby creating a gap cluster between any two selected clusters. In the second selected
cluster a coin toss determined whether T
was delivered or all selected households were left as
controls. The third selected cluster was then given the opposite treatment of the second cluster.
This way we ensured that two selected clusters would never be geographically contiguous.
A typical sample village had about 7 study clusters and 11 geographical clusters in all, including
gap clusters. The final sample has 67 clusters in total, 30 assigned to T
, 27 assigned to T
and 10

These statistics are also consistent with Pakistans rather dismal performance on a range of development
indicators. According to the 1998 Human Development Report, for example, Pakistan ranked 138 out of 174 on the
Human Development Index (HDI), 131 out of 163 on the Gender Development Index (GDI), and 100 out of 102 on
the Gender Empowerment Measure (GEM).
While RCONs team members were new in the villages, MRDO staff had been working in the area, although their
coverage was still low. According to Table 1, only around 11 percent of the women in the sample were MRDO
members. We ensured, however, that MRDO staff did not conduct the campaign in the villages where they had been
working previously. MRDO staff was also not engaged in the collection of the follow-up data. When asked
informally about whether women in the household they had visited to deliver the campaign had voted and for whom,
they did not know. As a result, it is clear that MRDO staff did not have any authority over the household and there
was no expectation that they would obtain future favors if they casted the vote.

left as controls.
Within each selected cluster, irrespective of the specific treatment, every 4

household was selected and surveyed, starting at either end of the cluster. In T
and T
all selected households were assigned to the respective treatment, with the exception of every 5

selected household, which was left as a control. This generated 2 to 4 controls in each T
and T

cluster in addition to the households selected in the control clusters. All women in a particular
household were given the same treatment. It is important to stress that the border of a given
cluster does not coincide with the beginning or end of a street or the village, since the location of
clusters were also randomly chosen. In other words, households in the periphery of the randomly
generated cluster are on average similar to households in the center of the cluster. This generates
exogenous variation in the number of treated households near each household that will be
exploited in some specifications.
In this regard, our paper is perhaps closest to Duflo and Saez
(2003) in that the peer group is fixed by location and only a subset of the peer group in a
treatment cluster is treated. In total, 2,735 women from 1,018 households were reached. Figure 2
displays a section of a study village containing three clusters delimited by a white solid line.
Notice that some of the boundaries of the cluster do not coincide at all with the natural
boundaries of the village. The dots, squares, stars and triangles indicate the location of the study
households. A dot denotes a household in a control cluster, a square (star) denotes a treated
household in a T
) cluster and a triangle is a control household in a treated cluster (either T

or T
). These three clusters are mapped to a polling station whose location falls outside the map.
During the door-to-door visit, basic data on each sample household was collected, including the
GPS location of the house, a basic roster of all adult women with their past voting record and the
name and address of their closest friend or confidant in the village. The door-to-door visit lasted
about 20 to 25 minutes for treated households and 5 to 10 minutes for control households. All
households were found, although in a few cases a repeat visit took place on the same day. None
of the households refused to participate in the awareness campaign or to be interviewed.

We kept one randomly selected control cluster in the survey sample per village. In one larger village, two control
clusters were included in the survey.
A comparison of households in the periphery to those in the center, defined by whether or not they are closer than
the median household to the cluster center, yields no significant differences among the 12 household characteristics
of Panel B in Table 1. Alternatively, we regress an indicator variable, which takes the value 1 if the households
distance to the cluster center is smaller than the median household distance to the cluster center on all 12 household
characteristics. The p-value of an F-test that all household variables are jointly zero is 0.83. We therefore conclude
that the location of the cluster center is random and that households in the center and periphery of the cluster are

Instead of relying on self-reported voting behavior, we verified it by taking advantage of a

requirement in Pakistan of marking a voters finger with indelible ink.
To assist the canvassing
team with the post-election verification, a local woman in each village, usually a primary school
teacher, was also identified during the awareness campaign. This woman was provided the list of
sample women whose finger ink stain had to be verified on Election Day and the day after the
election. This list included one confidant from each household. The confidant was selected as
follows: in every even numbered household, the confidant of a woman who was either a daughter
or a daughter in law of the household head was selected, while in every odd numbered
household, the confidant of the household head (if the head was a woman) or the heads wife,
sister, mother or aunt was selected. Not all households yielded at least one eligible woman
using this rule, so the final sample includes 727 confidants whose vote was verified.
Voting verification took place between the evening of February 18
, Election Day, and the
evening of February 19
. The field teams visited each village on February 19
to check 10
percent of the verifiers assignment at random and found no significant differences.
During the verification exercise, the verifiers were unable to locate 98 women (and 27
households). This leaves us with a sample of 2,637 women and 991 households. We were able
to verify all 727 confidants.
Attrition is therefore quite low, with roughly 3% of households not reached during verification. It
is also unrelated to treatment assignment (see Panel A of Appendix Table A3), though
households in T
clusters are somewhat more likely to attrit (see Panel B of Appendix Table A3).
In addition, 158 women claimed to have cast a vote but did not have the requisite ink mark. To
be conservative, we treat these women as not having voted, although the results do not change if
we consider them as voters.
Verification was followed by a post-election survey of the same 2,637 women in March 2008.
We ensured that the team of enumerators that visited a given household at follow-up was
different from the one that had delivered the awareness campaign. The survey collected
information on household demographics, recall of the door-to-door visits, access to and use of

The Representation of the People Act of 1976 states in Paragraph that the voter shall be required to
receive a personal mark, made with indelible ink, on any finger of either hand as indicated by the Commission.

various media, and knowledge of the balloting process and political candidates, among other
issues. Finally, we collected the official electoral results by gender, candidate and political party
for each of the 21 polling stations that served our sample villages.

Average turnout among women in our sample is 59 percent, while female turnout in the 21
polling stations is 47.3 percent. At the constituency level, total turnout was 39.2 percent in
Khairpur and 48.6 percent in Sukkur. The corresponding turnout rate (i.e., by district and
including both males and females) in the sample polling stations was 41.7 percent and 43
percent, respectively. While there is significant variation in contestation at the polling station
level, the share of PPPP at the constituency level was a large 70 percent in Khairpur and 73
percent in Sukkur.
Table 2 reports the difference in means of household and woman characteristics across different
samples. See Appendix Table A1 for the definition of the variables used in the paper. Column 1
in Panel A compares treated households to all control households, irrespective of whether they
live in treated or control clusters. Columns 2 and 3 compare T
and T
households, respectively,
to all control households. Column 4 compares all households in treated clusters (both treated and
control households) to those in control clusters, Column 5 compares treated households to
households in control clusters only and finally Column 6 compares control households in treated
clusters to households in control clusters. Overall, there is little difference in household
characteristics across samples. Treated households have a little more land than control
households in some comparisons, but no difference in assets or housing quality. The P-value of
an F-test that all variables are jointly insignificant can never be rejected. In Panel B, the same
comparisons are reported for woman characteristics. Women in treated households are somewhat
younger in some comparisons and have more young children as a result. They also appear to
have less access to cable TV, perhaps due to their lower mobility. An F-test that all woman level
variables are jointly insignificant cannot be rejected in 4 out of 6 comparisons. However, to
alleviate any concerns regarding balance, we always control for the household and woman
characteristics that lack balance across treatment and control groups.

Results by gender are tabulated at each polling station. This is possible because polling areas and polling booths in
Pakistan are separated by gender.

Appendix Table A4 suggests that the intervention was successfully implemented: all treated
women correctly recall having received a visit in which information about the electoral process
was provided. Almost all women in the T
treatment group correctly recalled that the issues
raised during the visit concerned the importance of voting while 70 percent of women assigned
to the T
treatment group correctly recalled that the visit included information on the importance
of voting and the actual balloting process. In contrast, control households recall a visit but none
report having received information about the electoral process. Finally, control women in treated
clusters are far more likely to report talking to their neighbors about political issues related to
party or candidate positions and the importance of voting in accordance with ones own
preferences, providing the first piece of evidence of information spillovers.
Follow-up data also suggest that there were no major incidents during Election Day in the study
Virtually all sample women had possession of their National Identification Cards
(NICs) before they left for the polling station and ninety percent of the women who voted also
found that the instructions in the polling station were appropriately displayed and that no one
else was present inside the booth when they cast their vote. While most women (61 percent)
report travelling to the polling station by foot, a substantial number (26 percent) report using
transportation provided by a political party, which is legal in Pakistan. However, almost all
women went to the polling station with others. Most were accompanied by other female
household members (62 percent) or went with their spouse or another household male (11
percent). However, a significant number also went with a female friend or relative (25 percent).

3. Empirical Strategy and Results
3.1 Turnout and Information Spillovers
Because treatment is assigned randomly at the geographical cluster level, its impact on female
turnout can be estimated e following OLS regression equation: via th

= [I


In contrast, media reports from the northwest of the country indicate that several female polling stations remained
empty because village elders actively prevented women from voting (AP, February 18th, 2008).

indicates whether woman i in household h in cluster c in polling station p in village
v is verified as having voted (1=Yes), I
is the treatment indicator (1 if woman i in household
h in cluster c in polling station p in village v received the voting awareness campaign), and
is a vector of polling station, household and individual woman characteristics. We follow
Bruhn and McKenzie (2009) and include household and woman characteristics from Table 2 that
lack balance (total land owned, age, access to cable, number of children under 5 years old) as
well as variables which are likely to influence voting behavior such as zaat (caste), having an
NIC, mobility, schooling and whether the women seeks advice from a religious leader or Pir.

Finally, we include in X
the total number of women registered to vote in the polling station.
Inclusion of X
corrects for baseline imbalances and increases efficiency by absorbing
residual variation in the data.
We also include a village fixed effect u

to remove the influence

of village specific unobservable characteristics. The term e
is a mean-zero error. Since the
unit of randomization is the geographical cluster, standard errors are always clustered at this
level (Moulton 1986).

A modified version of Equ 1) measures the effect of T
and T
separately: ation (

= [ +[

The coefficients [
anu [
capture the impact of treatment on turnout and are the main
coefficients of interest.
Table 3 reports the results. In order to capture the importance of within cluster spillovers, we run
Equation (1) in Panel A and Equation (2) in Panel B using four different subsamples. In column
1, we simply compare treated women to all control women, regardless of their location
(comparison T-C). This comparison ignores spillovers altogether by grouping control women in
treated clusters together with (control) women in control clusters. In column 2, we compare
treated clusters with control clusters (comparison T
). Here treated and control women in

Although the NIC is required to vote, some women in our sample were verified as having voted, though they did
not have an NIC.
Some of the variables were collected at baseline, prior to the campaign, while others were collected in the follow
up survey but for existing values before the intervention. As a result, none of these characteristics could be affected
by the campaign.

We note that in some households several women were treated. We are agnostic about the intra and inter
household correlation within a cluster and thus decide to allow for a unique within cluster correlation.

treated clusters are grouped together. In column 3, we compare treated women in treated clusters
with women in control clusters (comparison T-C
). We therefore drop from the analysis control
women in treated clusters. Finally, in column 4 we compare control women in treated clusters to
women in control clusters by dropping treated women from the analysis (comparison C
). If
spillover effects are important, the coefficient of interest in the first (nave) comparison should
be smaller since control women in treated clusters are likely to have been influenced by treated
We indeed find that the nave estimate in column 1, panel A, is lower than that of columns 2-4
by 6 percentage points. Thus, accounting for within geographical cluster spillovers increases the
impact of treatment to about 12 percentage points. More importantly, control women in treated
clusters are about as likely to vote as directly treated women.
In Panel B, the pattern of lower
estimates in column 1 compared to those in columns 2-4 is repeated and, as expected, estimates
for the impact of T
are larger. They are also more precisely estimated, although we are unable to
detect statistically different effects between T
and T

While this strategy allows us to assess spillovers within treatment clusters effectively, it does not
account for spillovers beyond the geographical cluster. It is plausible that women talk to other
women outside the geographical cluster, especially women located near the boundary of the
cluster. The design included gap clusters to ensure that control clusters were isolated from
treated clusters, but women in these control clusters might have been affected directly or
indirectly by the intervention and, as a result, even the estimates of columns 2-4 in Table 3 could
be downward biased.
We use two strategies to assess spillover effects beyond the geographical cluster. First, we use
the GPS location of every household in the study to compute the number of other treated and
control households within a given distance radius and run the following OLS regression

A regression that includes both a treatment dummy and a dummy for control households in treated clusters shows
that the coefficient on the treatment dummy is 0.117 and the coefficient on the dummy for control households in
treated clusters is 0.124, though neither coefficient is statistically significant at conventional levels. The P-value of
the t-test that both coefficients are equal is 0.798.
The impact of information on turnout for friends is in the same range as that for other control women in treated
clusters, ranging from 10 to 12 percent. This is not surprising given that the vast majority of confidants reside in the
same cluster as the woman who identified them as her friend.

= [I

where C
is an indicator for whether household h is not treated but has at least one treated
household within a distance radius of d meters, and N
is the total number of surveyed
households within distance radius d of household h.
According to Table 1, the average distance
between any two households in a cluster is 194.2 meters (0.12 miles) and the median distance is
roughly 100 meters. In contrast, the median distance between any two surveyed households in a
village is roughly one kilometer (0.67 miles). We consequently use a radius of 75, 100 and 200
meters, which corresponds roughly to the 25
, 50
and 75
percentile of the distance between
any two households within a cluster. The rest of the terms are as defined in Equation (1), and as
before, standard errors are clustered at the geographical cluster level. The coefficients of interest
are [ and 0. This specification allows for a simple test of the extent to which female turnout
among control households near treated households resembles female turnout among directly
treated households.
Panel A of Table 4 reports the results from Equation (3). The treatment effects are robustly
significant and range between 12 to 15 percentage points. The estimate of 0 is also significant in
columns 1 and 2, and is comparable to the direct treatment effect, suggesting that geographical
spillovers are large. Indeed, the t-test for [ = 0 is never rejected. The coefficient on the number
of households within a given radius, which can be interpreted as household density, is significant
in columns 2 and 3, suggesting that turnout is higher in more densely populated areas within a
village, perhaps because polling stations tend to locate there. Panel B reports the results for the
OLS regression equation analogous to Equation (2). We again find that the direct (and indirect)
effect of T
is somewhat larger than that of T
but the difference is, again, not statistically
significant, at conventional levels, in our sample.
The other strategy we use to study spillover effects beyond the geographical cluster is inspired
by Kremer and Miguel (2001). In order to assess how treatment density within a given radius
affects turnout, we rely on exogenous variation in the local density of treated women, by virtue


It is clear that the dummies I
and C
cannot both take value 1, since households are either treated or not.
Both dummies take value zero if the household was not treated (I
= u) and was located more than d meters
from the closest treated household.
of the cluster level randomization.
Specifically, we construct non-overlapping concentric rings
that are 200 meters wide around each sample woman. For each ring (or band) we compute the
number of treated women within the band, as well as the total number of sample women. Since
the median distance between any two households in the village is about one kilometer, the bands
start at eters. The regression specification in this case is 0-200 meters and extend up to 1,200 m
= [I
+ (o

where NI
is the number of treated women between distance d and D from each sample
woman, and N
is the number of women interviewed between distance d and D from each
sample woman. The rest of the terms are as defined in Equation (1) and standard errors are
clustered at the geographical cluster level.
The estimates for o
can be used to estimate the average spillover gain for sample women from
having treated women residing in close proximity. The coefficients are reported in Column 2 of
Table 5. Spillover effects are significant up to 1,000 meters. The number of treated women
ranges from 0 to about 161 women, with the largest number of treated women in the 0-200 meter
range. Columns 1 and 2 in Table 5 report the mean and median number of treated women. Using
only the coefficients that are significant, we estimate a mean increase in the odds of voting of 68
percentage points and a median increase of 45 percentage points.
Consistent with our earlier
results, once proximity to other treated women is controlled for, the residual effect of being
directly treated is nil (i.e. [ = u). Clearly, social interactions among women with mobility
constraints are largely dictated by geographic proximity. Communication is easy and can happen
over laundry, cooking and childcare, which require little movement away from home.
Finally, we assess the size of information spillovers at the polling station level, using official
electoral results by gender. Using polling station level information allows us to look at spillovers
for all registered voters in the village and to check potential spillover effects of the information
campaign on both men and women. Sample villages have between 1 and 3 polling stations each

Kremer and Miguel (2001) assess cross-school externalities using exogenous variation in the local density of
treatment school pupils generated by the school-level randomization.

To see this, note that the spillover gain is the average number of treated women located within 0-200 meters times
the average effect of having an additional treated woman in this range (o
) plus the analogous spillover effects
due to treated women located between 200-400, 400-600, 600-800 and 800-1,000 meters from a woman.
and the average distance of households from their matched polling station is roughly one
kilometer (see Table 1). The outcome of interest in this case,
, is the turnout rate in polling
station p in village v, that is, the number of votes cast by women (men) divided by the number of
registered women (men). Correspondingly, the impact of treatment, SI
, is the share of treated
women measured as the number of women treated in polling station p in village v divided by the
number of registered women.
Recall that the intervention took place after the voter registration
period, ensuring that registration is orthogonal to treatment assignment. We include a vector of
polling station level variables, X
to control for polling station level differences. This yields the
followin re s ca : g gression pecifi tion

= o
Columns 1 and 2 in Panel A of Table 6 show that an increase in the share of treated women in
the polling station increases female turnout by 86 to 99 percentage points, depending on whether
polling station controls are included. In contrast, there is no effect for male turnout (Table 6,
columns 3 and 4). The fact that men are not influenced by information provided to women could
reflect mens greater exposure to political information, wider networks or simply lack of
effective communication between men and women on political issues.
These polling station - level results provide further confirmation of the size and significance of
the spillover effects among women found in Table 3, 4 and 5. There are however differences in
the estimates because for two reasons. First, as Table 5 shows, women may have been influenced
by other women beyond the radius we consider. Second, and perhaps more importantly, Tables
3, 4 and 5 report estimates of increases in the probability of voting for women in our sample,
while the estimates of Table 6 include the effect of treatment and spillovers on all women
registered to vote in the polling station, regardless of whether they are in our sample.
We can in fact use these polling station-level results and those of Table 5 to infer the minimum
number of untreated women that would have been influenced by treatment to reconcile both sets


The variable SI
ranges from 0 to 0.77.
of estimates. We aggregate a version of Equation (3) up to the polling station level and equate it
to rs n o quat n (5 at includes the same controls.
This gives a ve io f E io ) th
, which yields



Since = is never rejected (see Table 4), this implies



Plugging in the estimates for the various distance radiuses considered, the number of affected
untreated women ranges between 6 and 8. Because every 4th household was selected to
participate in the study, it is reasonable that treated women in treated clusters would talk these
many untreated neighbors.

3.2 Candidate Choice
We now turn to the impact of the awareness campaign on candidate choice. Table 7 reports the
results of specifications (1) and (2) above where
now indicates whether woman i in
household h in cluster c in polling station p in village v reported voting for PPPP and is verified
as having voted. The number of observations is lower relative to Table 3 because only females
verified as having voted are included in the regressions. As before, the estimates in column 1
compare treated households to control households in both treated and control clusters. They do
not account for spillover effects and as a result, the coefficient is about one third smaller in
magnitude than those of columns 2-4 which do account for spillover effects. Panel A shows that
on average, the campaign reduced the probability of voting for PPPP by about 15 to 22

In particular, we run Equation (5) with weighted averages of the individual controls of Equation (3). In this
specification, the coefficient on the share of treated women SI
is 1.07 and significant at the 2 percent level.

percentage points. In Panel B, the impacts for T

are again larger in absolute value and more
precisely estimated than those of T
, but we cannot reject the null that the estimates are equal.

Columns 1 and 2 of Panel B of Table 6 confirm these results at the polling station level. The
share of treated women in a polling station reduces the PPPP female vote share. In particular, a
10 percent increase in the share of treated women in a polling station leads to a reduction of 6
percent in the share of PPPP female votes. Similar to the turnout results of Panel A, columns 3
and 4 of Panel B show that the campaign had no effect on the PPPP male vote share. Given that
the awareness campaign did not mention any candidate or party by name, the fact that it appears
to have affected not just turnout, but also party vote shares is remarkable and could have
important policy consequences. One plausible explanation for the impact on the party vote shares
is that in an environment where one party (the PPPP) was likely to get a landslide, the campaign
may have induced women supporters of PML-F to vote in greater numbers, thereby increasing
the share of PML-F, although the PML-F is not reputed to be a pro-women party.
With these results in hand, we now turn to a more direct test of the relevance of the information
content of the campaign by assessing the quality of information acquired by the male head on the
candidate choice of women in his household. In the follow-up survey, the male head was asked
about whether or not each woman in the household had voted and, if she had, whom she had
voted for. The same information was solicited from each woman about all the other women in
the household. Using these unique data, we can check the extent to which these cross-reports,
i.e., the reporters choice of candidates for a woman, are in agreement with the candidate choice
reported by the woman herself. The indicator of agreement takes the value 1 if the two reports
match, and is zero otherwise.
Candidate choice information is available for all women who

The point estimate for control women in treated clusters (column 4) is also larger than the point estimate for
women in treated households (column 3), though this difference is again not statistically significant (p-value of a t-
test that the coefficients are equal from a pooled regression of Panel A is 0.20). This may suggest that treated
women exert more influence on untreated women than on other treated women and that they talk not only about the
information campaign but also about their candidate choice, as reported in Panel B of Appendix Table A4.
If the reporter stated that a woman did not vote when she reported voting and was verified as doing so, the
agreement indicator is coded as missing. This is the case for less than 5 percent of the reports by men and roughly
one percent of the reports by other women. Likewise, if the reporter answers I dont know when asked whom a
given woman voted for, we code the agreement indicator as missing. This is the case for 7 out of 1,421 reports by
men (less than 0.5 percent) and only one report by other women. We follow this approach because lack of
knowledge about a womans voting behavior could reflect either indifference or freedom to select whomever she
desires. Given the low percentage, results do not change if we recode them with a value 0. Note that out of the 1,220
women who report having voted, and were verified as doing so, only one declined to answer whom she voted for.

self-report that they voted, but we restrict the sample to women who were verified as having
voted. The final sample includes 3,713 cross reports and 1,220 women, with the number of
observations per woman varying by household size.

If the campaign successfully conveyed information on the secrecy of the ballot then household
members, and particularly the male head, should have less information on the candidate choice
of wo n in th eho test t ion me e hous ld. We his with the following regress
+ [
- E
) + yX

where H
is an indicator that takes the value 1 if the report of individual i on individual js
choice of candidate is correct (according to js self-report); E
is an indicator for whether
reporter i is the male head; and X
is reporter is vector of polling station, household and
individual characteristics. The error term is likely to be correlated across all observations with
the same reporter i and reportee j, but we still cluster standard errors at the geographical cluster
level, which is more conservative than using QAP (Krackhardt, 1988) or the correction in
Fafchamps and Gubert (2006).
The results are presented in Table 8. The coefficient of interest is [
which captures the
differential effect of treatment on the quality of male reports about the candidate choice of
women in the household. The results indicate that treatment reduces male knowledge about
womens chosen candidates by about 8 percentage points. As before, effects are larger and
measured more precisely for T
. Interestingly, the reduction in male knowledge is larger and
significant for controls in treated clusters (column 3) and is the only instance where the effects
for T
are significantly different from T
(p-value=0.067). These results are consistent with
reported conversations on political matters with neighbors in Panel B of Table A4. Controls in
treated clusters are far more likely to discuss political issues with their neighbors as compared to
women in control clusters and are equally likely to do so when compared to directly treated
women. This confirms the importance of the information provided in the campaign. Even the

Among the 2,637 women in the sample, 1,543 were verified as having voted. The discrepancy in the sample size
come from the fact that 21 percent of women that were verified as having voted, self-reported as not having done so.
These women appear as voters in the turnout analysis of Table 3 but are not used in the analysis of candidate choice
because we do not know whom they voted for. Interestingly, we also find evidence of conformity bias (Silver et al.,
1986; Harbaugh, 1996) since treated women that had not voted are significantly more likely to self-report as having
done so compared to women in control clusters (40.6 percent vs. 34.8 percent, p-value= 0.001).

more nuanced message about the secrecy of the ballot was apparently conveyed to women not
directly treated.
Table A5 complements these results by assessing the extent to which the electoral behavior of
women corresponds to that of their household head. Comparing treated women with women in
control clusters (column 1 and 2) we find that treated women are far more likely to vote for a
party (candidate) other than the one selected by the male head (from 2.8 to 10.1 percentage
points). We then check whether the information campaign affected women who had no prior
voting experience. The results in columns 4-9 suggest that this is not the case since the
intervention increased independent choice mainly among women who had voted in the past. As it
turns out, women without a prior voting history are also much less likely to possess NIC cards or
be registered to vote and are significantly younger. Given that the time between the information
campaign and the election was too short to allow for the acquisition of an NIC or a change in
registration status, this is perhaps not surprising. However, it is also possible that these women
face other barriers to participation.
3.3 Knowledge and Perceptions
An important question, given the large effects we find on turnout and candidate choice, is the
extent to which the campaign affected womens knowledge about political issues, perceptions
and behavior other than voting. Each cell in Table 9 reports the coefficient on the treatment
dummy from a regression analogous to Equation (1). The dependent variables are the average of
two knowledge questions on current events, an index of pro democratic views, for example
disagreement with "Only the educated should vote" and disapproval of various forms of
government such as "Only one party is allowed to stand for election and hold office" or "The
army comes in to govern the country". (Appendix Table A1 describes all variables in detail). A
higher index is associated with more pro-democratic views. We consider three additional
questions: whether the woman checked her name in the voter list after the intervention and
before Election Day; whether the woman believes that elections were free and fair and finally
whether the woman had witnessed or heard about instances of violence in the village.
The results indicate that treated women were more likely to check if their name was in the voter
list but were not more knowledgeable about current events nor did they have more pro-

democratic views. Interestingly, column 5 suggests that treatment increased the belief in the
legitimacy of the voting process as women in treatment clusters were more likely to report that
elections were free and fair. Column 6 is consistent with evidence of cognitive dissonance in
voting as women in control clusters were more likely to report instances of violence. Given that
control clusters were randomly located in the village, it is hard to believe that violence was
concentrated precisely in these clusters. Rather, women in control clusters seem to justify their
(non-)voting behavior ex-post by reporting more security concerns.
4. Cost-Benefit Analysis
The estimates from tables 3 and 6 can be used to evaluate the cost effectiveness of the
information campaign. The initial development of the campaign cost $3,600. The training of the
canvassing team cost $753 and the delivery of the information campaign cost $5,671. This last
amount includes the costs of collecting basic information about treatment and control households
which would not be incurred in practice if research was not being conducted. Since roughly two-
thirds of sample households were treated, we impute the costs to include 2/3rd of this amount in
the intervention cost. This gives us a total intervention cost of roughly $8,130, including the
costs of developing the information campaign and training enumerators. This is an overestimate
since the development of the information campaign and the training of canvassing teams
represent a fixed cost that can be sizeable if the scale is small. In our case, it constitutes over 50
percent of the overall costwhich if the campaign were scaled up, would be distributed over a
much larger population base. We therefore present the cost under two scenarios: inclusive of the
development of the campaign and enumerator training costs; and based only on the labor and
transport costs of delivering the campaign.
Since we have about 673 treated households, we get a cost of about $5.6 per household using
variable costs only, and $12 per household if we include fixed costs. This implies a cost per vote
of $2.3 ($4.9 if we include fixed costs).
To see this note that a household has 2.7 women on
average, so we treat about 10 women for every 3.7 households visited. Since the cost of treating
3.7 households is about $21 ($44 if we include fixed costs), and this yields 9 additional votes, the

This is about Rs. 201 (Rs. 453 including fixed costs), using the exchange rate in February 2008.

implied per vote cost is about $2.3 ($4. 9). If we ignore spillover effects and use woman level
estimates, we would obtain a cost per vote of $17.5 ($36.7).

5. Conclusions
This paper examines the role of pre-election voter information campaigns in inducing broader
participation in one of the largest new democracies of the world. We focus on two related
questions. First, does a lack of information on the electoral process and voting procedures
constitute an important barrier to political participation by women? Second, to what extent can
social interactions among women be instrumental in fostering participation beyond those directly
targeted by the information campaign?

We find overwhelmingly positive answers to both questions. Turnout among women that
received the information campaigned increased by about 12 percentage points on average, which
amounts to little more than one additional female vote for every 10 women or about 4
households treated. We also find evidence of independent candidate choice. In treated
households, men were significantly less likely to correctly assess the candidate choices made by
women in their households. In addition, treated women were more likely to vote for a different
party than the male head, especially among women who had voted in the past. Treated women
also voted in larger numbers for PML-F which was seen as less likely to win, thereby changing
the vote share of the losing party in sample polling stations. This is perhaps even more
remarkable given that the field teams were mostly PPPP supporters. This suggests that the
intervention empowered women and thus may have modified the rational calculus of voting
(Downs, 1957) by including a utility gain from the mere act of voting (Riker and Ordeshook,
1968). Consistent with this utility gain from voting, women in the randomly assigned control
clusters are more likely to report that elections were unfair (and to recall higher instances of
violence) in an attempt to justify not casting a vote ex-post. Among women who had not voted in
the past, the campaign proved to be less effective. More intensive interventions may be required
for such women, including assistance with voter registration.

Green and Gerber (2004) provide a nice summary of the price-per-vote in the US using various methods. They
estimate the cost of a vote in door-to-door campaigns, which are perhaps closest to what we do, to be around $19 per
vote using contract labor but ignoring spillover effects.

We also find evidence of large spillover effects dictated by geographic proximity. Control
women in treated clusters respond to cluster treatment assignment about as much as do directly
treated women. Moving beyond clusters we examine spatial spillovers more generally and find
still larger peer effects. The importance of spillover effects and peer pressure resonates well with
the theoretical literature on voter turnout that emphasizes the role of the group in coordinating
participation either because group members are rewarded by leaders or because they each believe
they are ethically obliged to vote and reinforce one another (see Shachar and Nalebuff, 1999 and
Feddersen, 2004 for a review).

The presence of significant spillovers also alters the cost benefit analysis quite substantially. An
additional vote costs more than seven times as much in the absence of spillovers. Given the
relatively low cost of an additional vote ($2.3, using variable costs only), once spillovers are
accounted for, information campaigns appear to provide a relatively cost effective mechanism
for enhancing the participation of rural women in the democratic process.

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Figure 1: Timeline
Feb 18 Feb 18-19 Feb 5 -15 March 5-25
HH visits and



Figure 2: Section of Village with geographical clusters

Notes: The solid white lines delimit a geographical cluster. A square represents the location of a T
household, a
star represents a T
household and a dot represents a control household in a control cluster. A triangle represents
a control household in a treated cluster (either T
or T


N.Obs Mean St.Dev Pct10 Pct.50 Pct.90

Numberofwomenregisteredineachpollingstation 21 434.0 196.7 195.0 464.0 656.0
Numberoftreatedwomenineachpollingstation 21 89.0 54.2 34.0 82.0 150.0
Shareoftreatedwomen 21 0.24 0.19 0.07 0.22 0.43
Turnoutforwomen 21 0.58 0.27 0.30 0.54 0.91
Turnoutformen 21 0.49 0.15 0.32 0.51 0.66
ShareofPPPPamongfemalevoters 21 0.62 0.26 0.39 0.66 0.88
SharePPPPamongmalevoters 21 0.63 0.25 0.33 0.67 0.93
Percentageofwomenwithaccesstocableinthepollingstation 21 0.34 0.26 0.06 0.23 0.75
St.Devofassetindex 21 1.76 0.30 1.46 1.72 2.09
St.Devofdistanceindex 21 0.79 0.52 0.16 0.69 1.31
Householdsize 963 10.2 5.17 5 9 16
991 2.69 1.48 1 2 5
AssetIndex 963 0.00 1.85 2.03 0.49 2.66
Totalownedland(inacres) 963 2.58 7.55 0.01 0.04 7.02
Averagemonthlyexpenditure(inRs.thousands) 963 8.80 4.71 3.00 9.00 12.50
Housequalityindex 963 0.00 1.38 1.62 0.32 1.97
LowZaatStatus 963 0.26 0.44 0 0 1
Receivedvisitfrompoliticalpartystaffpriortoelection(1=Yes) 963 0.75 0.43 0 1 1
Attendedpoliticalrallybeforeintervention(1=Yes) 963 0.24 0.43 0 0 1
991 0.97 0.91 0 1 2
Distancebetweenhouseholdswithingeographicalcluster(meters) 8,263 194.2 283.9 27.9 107.1 456.5
Distancebetweenhouseholdswithinvillage(meters) 48,430 1,472.9 1,304.9 109.4 1,070.5 2,962.8
Age 2,637 37.76 16.09 20 35 60
Womanhasformalschooling(1=Yes) 2,637 0.18 0.39 0 0 1
Womanismarried(1=Yes) 2,637 0.80 0.40 0 1 1
Numberofchildrenunder5yearsold 2,637 0.86 1.19 0 0 3
WomanhasaNationalIdentityCard(NICorCNIC)(1=Yes) 2,637 0.70 0.46 0 1 1
2,735 0.70 0.46 0 1 1
Accesstoradio(1=Yes) 2,637 0.48 0.50 0 0 1
AccesstoTV(1=Yes) 2,637 0.70 0.46 0 1 1
Accesstocable(1=Yes) 2,637 0.30 0.46 0 0 1
MobilityIndex(0to3) 2,637 2.17 0.42 2 2 3
WomanallowedtojoinanNGO(1=Yes) 2,637 0.73 0.44 0 1 1
2,735 0.11 0.31 0 0 1
Womanseeksadvicefromareligiousleaderor"Pir"(1=Yes) 2,637 0.64 0.48 0 1 1
Householdsize 0.266 0.289 0.227 0.412 0.422 0.371
(0.334) (0.382) (0.400) (0.433) (0.417) (0.546)
0.096 0.11 0.088 0.054 0.074 0.044
(0.104) (0.123) (0.114) (0.145) (0.139) (0.165)
Assetindex 0.017 0.061 0.036 0.086 0.063 0.188
(0.132) (0.146) (0.181) (0.204) (0.202) (0.195)
Totalownedland(inacres) 1.018** 1.360** 0.6 0.754 0.943 0.16
(0.428) (0.528) (0.512) (0.543) (0.572) (0.388)
Averagemonthlyexpenditure 473.211 470.616 444.17 267.484 367.439 297.676
(403.795) (441.530) (440.550) (591.398) (608.246) (510.030)
Housequalityindex 0.054 0.078 0.023 0.211* 0.192 0.314**
(0.098) (0.121) (0.117) (0.117) (0.117) (0.138)
Distancetopollingstation(Km) 0.013 0.036 0.011 0.137 0.108 0.277*
(0.081) (0.082) (0.115) (0.137) (0.129) (0.162)
LowZaatstatus 0.026 0.014 0.034 0.063 0.061 0.086
(0.059) (0.070) (0.067) (0.101) (0.099) (0.069)
(1=Yes) 0.000 0.002 0.002 0.007 0.006 0.015*
(0.007) (0.010) (0.008) (0.010) (0.010) (0.009)
Attendedpoliticalrallybeforeintervention(1=Yes) 0.032 0.003 0.070* 0.050 0.051 0.043
(0.034) (0.036) (0.040) (0.044) (0.045) (0.049)
N.Observations 972 676 588 972 845 292
PvalueFtestjointsignificance 0.340 0.635 0.971 0.799 0.754 0.466
** ** **
Age 0.730 0.872 0.674 1.410** 1.382** 1.533**
(0.167) (0.139) (0.272) (0.028) (0.034) (0.033)
Womanhasformalschooling(1=Yes) 0.007 0.002 0.025 0.015 0.016 0.020
(0.723) (0.915) (0.274) (0.616) (0.587) (0.596)
Womanismarried(1=Yes) 0.007 0.020 0.005 0.017 0.016 0.019
(0.641) (0.229) (0.802) (0.243) (0.295) (0.416)
Numberofchildrenunder5yearsold 0.088* 0.114** 0.048 0.147*** 0.150*** 0.137
(0.061) (0.042) (0.415) (0.004) (0.002) (0.104)
WomanhasaNationalIdentityCard(NICorCNIC)(1=Yes) 0.027 0.021 0.033 0.042 0.043 0.035
(0.292) (0.505) (0.180) (0.228) (0.216) (0.274)
0.022 0.002 0.042* 0.036 0.037 0.034
(0.333) (0.942) (0.095) (0.232) (0.223) (0.307)
Accesstoradio(1=Yes) 0.011 0.032 0.014 0.014 0.008 0.045
(0.728) (0.362) (0.722) (0.757) (0.854) (0.324)
AccesstoTV(1=Yes) 0.022 0.041 0.000 0.026 0.028 0.028
(0.522) (0.247) (0.997) (0.630) (0.598) (0.598)
Accesstocable(1=yes) 0.059 0.064 0.045 0.118* 0.116* 0.116**
(0.175) (0.204) (0.365) (0.079) (0.080) (0.028)
MobilityIndex(0to3) 0.032 0.055 0.005 0.012 0.020 0.034
(0.456) (0.214) (0.920) (0.826) (0.710) (0.665)
WomanallowedtojoinanNGO(1=Yes) 0.003 0.008 0.020 0.022 0.019 0.033
(0.915) (0.762) (0.534) (0.506) (0.573) (0.363)
0.004 0.018 0.029 0.030 0.023 0.072
(0.870) (0.531) (0.371) (0.410) (0.508) (0.105)
Womanseeksadvicefromareligiousleaderor"Pir"(1=Ye 0.051 0.031 0.079* 0.057 0.062 0.043
(0.129) (0.424) (0.066) (0.246) (0.214) (0.414)
N.Observations 2,637 1,827 1,577 2,637 2,303 768
PvalueFtestofjointsignificance 0.294 0.057 0.440 0.401 0.305 0.001
(1) (2) (3) (4)
Treatment(T) 0.06 0.118 0.120* 0.121*
(0.045) (0.073) (0.071) (0.062)
Rsquared 0.18 0.19 0.19 0.21
0.034 0.095 0.094 0.109
(0.052) (0.077) (0.075) (0.070)
0.093* 0.145* 0.152** 0.135*
(0.048) (0.077) (0.074) (0.079)
Rsquared 0.18 0.19 0.2 0.21
N.Observations 2,637 2,637 2,304 767
N 0.52 0.52 0.52 0.52
Pvalue (T
0.223 0.308 0.229 0.752
1 2
0.223 0.308 0.229 0.752
Pvalue (FtestforjointsignificanceofT
0.146 0.159 0.106 0.152
75m 100m 200m
(1) (2) (3)
Treatment(T) 0.122* 0.153** 0.119*
(0.065) (0.074) (0.070)
0.105* 0.133* 0.072
(0.060) (0.071) (0.064)
Numberofhouseholdswithinradius 0.006 0.006* 0.004**
(0.004) (0.003) (0.002)
Rsquared 0.19 0.19 0.23
PValue (T=C
0.612 0.549 0.192
0.092 0.132* 0.12
(0.066) (0.070) (0.078)
0.146** 0.182** 0.167**
(0.063) (0.069) (0.075)
0.045 0.066 0.004
(0.054) (0.058) (0.060)
0.114* 0.149** 0.151*
(0.064) (0.071) (0.086)
Number of households within radius 0 005 0 005* 0 003*
Numberofhouseholdswithinradius 0.005 0.005* 0.003*
(0.004) (0.003) (0.002)
Rsquared 0.191 0.20 0.20
Pvalue (T
0.461 0.350 0.148
Pvalue (T
0.418 0.472 0.764
Pvalue (T
0.245 0.285 0.322
Pvalue (C
0.425 0.392 0.211
N.Observations 2,637 2,637 2,637
N 0.58 0.58 0.58
Mean Median Coefficients
(1) (2) (3)
Treatment(T) 0.037
Numberoftreatedwomenwithin0200radius 40.40 35.00 0.007***
Numberoftreatedwomenwithin200400radius 20.47 16.00 0.009***
Numberoftreatedwomenwithin400600radius 11.91 4.00 0.007***
Numberoftreatedwomenwithin600800radius 15.50 6.00 0.005**
Numberoftreatedwomenwithin8001000radius 11.08 1.00 0.005*
Numberoftreatedwomenwithin10001,200radius 7.88 0.00 0.002
Numberofwomenwithin0200radius 56.78 47.00 0.002**
Numberofwomenwithin200400radius 29.84 24.00 0.004***
Numberofwomenwithin400600radius 18.33 7.00 0.005***
Numberofwomenwithin600800radius 21.28 8.00 0.003*
Numberofwomenwithin8001000radius 15.81 4.00 0.004*
Numberofwomenwithin10001,200radius 11.50 0.00 0.000
Observations 2,637
Rsquared 0.234
(1) (2) (3) (4)
ShareofTreatedWomen 0.864*** 0.991*** 0.044 0.149
(0.259) (0.240) (0.187) (0.183)
Rsquared 0.370 0.601 0.003 0.247
MeanofDependentVariable 0.584 0.584 0.487 0.487
ShareofTreatedWomen 0.614** 0.614* 0.372 0.456
(0.277) (0.314) (0.290) (0.270)
Rsquared 0.205 0.237 0.127 0.080
MeanofDependentVariable 0.621 0.623 0.630 0.630
PollingStationControls No Yes No Yes
N.Observations 21 21 21 21
Women Men
(1) (2) (3) (4)
Treatment(T) 0.056 0.157*** 0.146*** 0.218***
(0.041) (0.052) (0.047) (0.077)
Rsquared 0.166 0.175 0.196 0.285
0.023 0.130* 0.114* 0.202**
(0.052) (0.069) (0.065) (0.091)
0.093 0.190*** 0.183*** 0.246***
(0.057) (0.057) (0.055) (0.090)
Rsquared 0.171 0.179 0.201 0.286
N.Observations 1,133 1,133 974 299
N 0.950 0.950 0.950 0.950
p g
N 0.950 0.950 0.950 0.950
Pvalue (T
0.328 0.403 0.346 0.652
Pvalue (FtestforjointsignificanceofT
0.264 0.005 0.004 0.017
(1) (2) (3)
Treatment(T) 0.007 0.015 0.024
(0.023) (0.025) (0.025)
Manreportingaboutwoman 0.012 0.010 0.021
(0.019) (0.019) (0.020)
ManreportingxT 0.085*** 0.082*** 0.104*
(0.027) (0.028) (0.054)
RSquared 0.065 0.069 0.125
0.016 0.026 0.012
(0.026) (0.028) (0.025)
0.002 0.003 0.024
(0.027) (0.030) (0.029)
0.012 0.010 0.021
(0.019) (0.019) (0.020)
0.064* 0.072* 0.025
(0.037) (0.039) (0.040)
0.107*** 0.093** 0.189**
(0.032) (0.035) (0.084)
Rsquared 0.064 0.070 0.126
N.Observations 3,713 3,200 914
N 0.983 0.983 0.983
Pvalue (T
0.475 0.431 0.688
Pvalue (MaleReportxT
0.313 0.659 0.067
2637 0.005 0.066 0.051* 0.070** 0.104**
(0.072) (0.041]) (0.030) (0.034) (0.044)
2304 0.012 0.069 0.053* 0.075** 0.101**
(0.070) (0.042]) (0.031) (0.033) (0.042)
767 0.025 0.046 0.048 0.060 0.122**
(0.094) (0.052) (0.035) (0.037) (0.049)
N 0.00 0.03 0.61 0.88 0.27
g y

Appendix A: Visit Script

Importance of Voting (T1)

Picture 1: Ask In your opinion, who do you consider responsible for the situation shown in this picture? If women respond that
politician, feudal lords, bureaucrats and influential personalities, etc. then clarify that in fact you may be responsible for this state.
Also, responsible are all those who do not cast a vote or choose a wrong candidate. You are the ones who empower them. Hence you
need to understand how you can individually affect the decision of who finds solutions to your problems/issues. Do realize your power
and importance of your vote?

Picture 2: Ask Could your one vote bring a change in your life? Explain that your vote is of great importance. Through this vote a
representative is elected. It is this elected representative who then sits in the provincial or national Assembly and makes decisions with
regard to what facilities are provided in your area with regard to education, health, security, roads, income earning options, etc.

Picture 3: Many women think that casting a vote makes no difference. Ask women what they think. If they respond that they are
women or are underprivileged and therefore it will make no difference, stress that every Pakistani vote is of equal importance,
regardless of whether the voter is rich or poor, male or female. If they as women do not cast their vote then individuals who have no
interest in women related issues may get elected. Tell the women that there is a lot of power in their vote. People consider that women
are weak. Should all Pakistani women begin to vote, their vote has the power to alter a Government!

Picture 4: Ask the women whether they are aware that when they cast a vote in the General Elections, they actually select two
members: one for the large assembly, which is known as the National Assembly on the green ballot paper; and the second for the
small assembly which is Provincial Assembly on the white ballot paper. Both the assemblies work separately, with different
domains and duties assigned.

Picture 5: Explain that the major responsibility of the members of the national assembly is legislation. Like setting-up laws for the
protection of women rights; establishing law for peace and stability in the country; relations with foreign countries and construction of
major roads. Reiterate that the color of ballot for the member of national assembly is green.

Picture 6: Ask women whether they know about the responsibilities of the members of the provincial assembly. Explain that
provincial assembly member has a more direct link to the area they live in. It is this members responsibility to ensure the provision of
facilities such as girls and boys schools, health centers, irrigation and small and home based industries. Remind women that the color
of ballot for the member of provincial assembly is white.

Remind women that in the pictures previously shown they must have noted that the members of National and Provincial Assemblies
are tasked with a lot of work for local and national progress. Ask women whether they think good candidates should have specific
qualities in order to be effective at their job. Encourage active participation. Then, show Picture 7 and list the characteristics of an
effective candidate: educated, well reputed, respected for their good character and benevolent to poor; interested to promote projects
that will reduce poverty; ability to understand problems; not misused national resources in the past; and have a positive attitude.

Ask women whether they have information about all the candidates that are contesting elections from their constituency. Show
Picture 8 and ask women about their impression. Explain that there may be many women who do not know about the candidates that
are contesting in their constituency. How then can they compare the qualities of the candidates in order to decide who is the best

Ask women if they would cast their vote. If Yes then ask how they would decide whom to vote for. Do they have enough
information about all the members? and Do they really know who the best candidate is? If Not then ask where they would obtain
information about the candidates. Show Picture 9 and tell them where information about the candidates could be obtained, e.g. male
members within the family (since they are more aware and exposed), neighbors, teachers/respected members of the community and
party workers.

Picture 10: Ask women what they see. The picture is self explanatory, showing a before and after behavior of a candidate before the
election the candidate is humble and attentive. After the election they just whisk off without even acknowledging your presence! Ask
the women if this has happened to them. Highlight that this happens when one does not get correct information about the member and
thus one chooses the wrong candidate. Ask women if they ever wonder why cast a vote when nobody has done anything for us so
far? Everyone is the same and all exploit resources. Tell women that they may have had bad experiences, but it is still important to
keep the electoral process alive. Show Picture 11 and explain that one can select the best amongst the lot and only then will better
candidates come forward. This would make clear to the member that you cast your vote sensibly. If this practice continues then soon

sincere people would also contest elections and we would vote for them because of their genuine attributes. (Just as shown in Picture

Secrecy of Balloting (T2)
Tell women that we have so far established that voting is important. But does everyone have to vote for the same person? Tell women
that even when two sisters go to the market to buy a dress, they generally come away with two different designs, colors, and fabric.
Why does this happen? Because people may have different preferences.

Explain that secrecy is a legal right and responsibility of every citizen. When you vote, you have the right to keep your vote
confidential. No one may see you cast your vote, not even the election commission staff, polling agent, or another voter. It is only if a
voter has a disability such as weak eyesight or a physical problem that can prevent you from stamping the ballot paper that you may
seek assistance. Otherwise, any other presence would be considered illegal. Lack of ability to read or write does not justify any kind of
assistance (since one does not need to read or write to understand the ballot paper). Show Picture 12 and explain the basic process of
balloting as follows: (i) Voter enters the polling station; (ii) Polling officer inspects National ID Card; marks thumb with indelible ink
and after calling the name and serial number of the voter, marks off her name from electoral list; (iii) The First Presiding Officer
issues a ballot paper for the national assembly. She stamps and signs it on the reverse side and marks the counterfoil; (iv) The Second
Presiding Officer issues ballot paper for provincial assembly. She stamps and signs it on the reverse side, and marks the counterfoil;
(v) Voter goes to the polling booth and stamps on both the ballot papers; (vi) Voter puts her ballot in the specified ballot boxes; (vii)
Voter leaves the polling station.

Tell the women that to keep voting confidential, all polling stations will be equipped with a Voter Screen. This screen will ensure that
no one sees you while stamping the ballot paper. Show Picture 13 and highlight that the Election Commission has undertaken special
arrangements to make voting easy for women e.g. separate polling stations for women, female polling staff, and ensuring that
polling stations and polling booths are located in easy to reach places, e.g. nearby schools.

Show Picture 14 and explain the right procedure of balloting. Show how the ballot should be stamped and more importantly folded,
and then put in the appropriate ballot box i.e. green ballot paper into green ballot box and white ballot paper into the white ballot box.

Ask the women, how many of them have voted before? Ask them how they have felt after casting the vote? Some may say nervous or
afraid while others may say satisfied. Show Picture 15 and explain that as shown in the picture, once a voter comes out everyone is
interested in knowing whom she has voted for. Tell the women that this should not make them anxious or nervous. If they want, they
can make everyone happy!

Appendix B: Visual Aids
















ShareValidVotes Shareofvalidvotescastbywomen(columns12)andmen(34)
SharePPP ShareofvotesobtainedbyPPPPoverthetotalnumberofvalidvotes
Shareoftreatedwomen calculatedbydividingthetotalnumberofwomentreated,inapollingstation,bythenumberofregisteredwomeninthepollingstation.
St.Devofassetindex StandardDeviationofhouseholdassetIndex
St.Devofdistancetopollingstation Standarddeviationofdistancetopollingstation
Pct.ofWomenwithAccesstoCableTV PercentageofWomenwithAccesstoCableTV
Householdsize Totalnumberofindividualsinthehouseholdincludingchildren
The first component of a PCAincluding the number of refrigerators, freezers, fans, geysers, washing machines/dryers, cooking stoves, TVs, VCRs, VCPs/ CD
players, Radios/ cassette players, sewing/knitting machines, dish antennas, cable services, bicycles, motorcycles, cows, buffalos and goats, as well as a
Totalownedland(inacres) Totalacresofownedlandbythehousehold
Average monthly expenditure computed using the mid point of the following options: less than 2,000, greater than 2,000 but less than 4,000, greater than
4,000 but less than 6,000, greater than 6,000 but less than 8,000, greater than 8,000 but less than 10,000, greater than 10,000 but less than 15,000, greater
Index constructed using principal components analysis using number of rooms and dummy variables that take value 1 if house has pacca walls, a roof made of
concrete, iron/brick/tile or wood/brick/tile, the toilet is flush connected to public sewerage, flush connected to pit or flush connected to open drain latrine
Distancetopollingstation(Km.) TotaldistanceinKm.fromhouseholdtopollingstation.
LowZaat(Caste)Status Householdbelongstoserviceormenialzaatgroups
Womanhasformalschooling(1=Yes) Dummyvariableequalto1ifwomanhasanyformalschooling.
Womanismarried(1=Yes) Dummyvariableequalto1ifwomanismarried.
Numberofchildrenunderage5 Numberofchildrenunder5yearsoldovertotalnumberofchildrenthatthewomanhas.
HasaNIC(1=Yes) Dummyvariableequalto1ifthewomanhasanationalidentitycard
Accesstoradio(1=Yes) Dummyvariableequalto1ifwomanhasaccesstoaradio.
AccesstoTV(1=Yes) Dummyvariableequalto1ifwomanhasaccesstoTV.
Accesstocable(1=Yes) Dummyvariableequalto1ifwomanhasaccesstocable.
HoursofRadioinanaverageweek Theproductofnumberofhoursofradiolistenedinanaveragedaytimesnumberofdaysrespondentlistenstotheradioinanaverageweek.
GetsWorldnewfromBBC'sUrduService Dummyvariableequalto1ifrespondentreportedturningtoBBCradiofirstforgettingworldnews
NumberofhrsofTVwatchedinavgweek TheproductofnumberofhoursofTVwatchedinanaveragedaytimesnumberofdaysrespondentwatchesTVinanaverageweek
Index based on questions about whether woman would be allowed to go to bazaars , doctors or for social visits outside her village and her settlement. 1= No
MRDOmembership(1=Yes) Dummyvariableequalto1ifwomanisamemberofacommunityorganizationinhervillage.
Index constructed using prinicipal components analysis of 3 questions on methods tried to resolve different situations for both men and women(election
officials left name off voter list, police wrongly arrested someone in family, someone wrongly seized family's land). The 3 questions were recoded to 1 if
Index constructed by adding 1 (0 otherwise) if the answers is YES to following questions whether during the past year he/she contacted a local government
Index constructed by adding 1 (0 otherwise) if the answers is YES to following questions whether during the past year he/she contacted a religious leader (Pir,
Dummy variable equal to 1 if respondent had heard about the imposition of the emergency rule, the removal of Chief Justice of the Supreme Court and the
Recallswinningcandidate(1=Yes) Dummyvariableequalto1ifwomanperfectlyrecalledthenameofthecandidatethatwontheNationalAssemblyseatinherconstituency
Recallsnamesofmaincandidates(1=Yes) Dummyvariableequalto1ifwomanperfectlyrecalledthenamesofthecandidatesfromthetwomainpartiesthatcontestedaNationalAssemblyseat
Votedinlastelections(local)(1=Yes) Dummyvariableequalto1ifwomanvotedinthelastlocalbodyelections.
VotedinFeb08(1=Yes) Dummyvariableequalto1ifrespondentvotedinthisnationalelections.
Elections were free and fair (1=Yes)
Dummy variable equal to 1 if woman believes that the national elections held in February 18th 2008 were "Completely free and fair" or "Free and fair, but
Dummy variable equal to 1 if woman confirmed in the followup survey that she was visited before the elections to tell her about the importance of the
Dummy variable equal to 1 if woman confirmed in the followup survey that she was present in the visit before the elections to tell her about the importance
Dummy variable equal to 1 if woman confirmed in the followup survey that she was present in the visit that took place in a neighbor's house before the
Dummy variable equal to 1 if woman confirmed in the followup survey that some neighbors were present in the visit that took place at her house before the
Dummy variable equal to 1 if woman confirmed in the followup survey that the issue raised during the visit before the elections was about the importance of
Dummy variable equal to 1 if woman confirmed in the followup survey that the issues raised during the visit before the elections were the importance of
Dummy variable equal to 1 if woman confirmed in the followup survey that she talked about the visit and the issues raised during the visit with others in her
Dummy variable equal to 1 if woman confirmed in the followup survey that some women from her neighborhood talk to her about the meeting which she
Female Male
(1) (2) (3) (4)
AccesstoRadio(1=Yes) 1,923 0.47 0.42 0.061
Numberofhoursofradiolistenedtoinanaverageweek 852 9.7 9.63 0.867
AccesstoTV(1=Yes) 1,923 0.67 0.629 0.103
NumberofhoursofTVwatchedinanaverageweek 1,222 15.3 11.0 0.000
AccesstocableTV(1=Yes) 1,923 0.29 0.23 0.008
ListenstoBBC'surduserviceforworldnews(1=Yes) 852 0.10 0.48 0.000
Shareofpoliticalpartysignscorrectlyidentified 1,923 0.28 0.42 0.000
Shareofpoliticalpartynamescorrectlyidentified 1,923 0.86 0.96 0.000
Knowsthegenderofmaincandidates(1=Yes) 1,923 0.95 0.98 0.483
Recallsnamesofmaincandidates(1=Yes) 1,923 0.82 0.86 0.488
Recallswinningcandidate(1=Yes) 1,923 0.90 0.95 0.219
AwareofEmergencyRule(1=Yes) 1,923 0.10 0.51 0.000
Attendscommunitymeetings(1=Yes) 1,923 0.18 0.52 0.000
Attendsdemonstrations(1=Yes) 1,923 0.12 0.23 0.000
Attendedpoliticalrallybeforeintervention(1=Yes) 1,923 0.05 0.24 0.000
Takes action
Ifnamemissinginvoterlist(1=Yes) 1,923 0.76 0.92 0.000
Ifpolicemistakenlyarrestfamilymember(1=Yes) 1,923 0.93 0.98 0.000
Iffamilylandisseized(1=Yes) 1,923 0.92 0.98 0.000
Indexofcommunityactiontaken 1,923 0.29 0.69 0.000
Contactslocalcouncilor(1=Yes) 1,923 0.25 0.37 0.000
Contactsalocalpoliticalpartyofficial(1=Yes) 1,923 0.22 0.38 0.000
Indexofformalauthoritycontact 1,923 0.10 0.34 0.000
Contactsareligiousleader(1=Yes) 1,923 0.66 0.49 0.000
Contactsatraditionalruler(1=Yes) 1,923 0.45 0.32 0.000
Indexofinformalauthoritycontact 1,921 0.12 0.30 0.000
PanelA:Treatment (1) (2) (3) (4)
Treatment(T) 0.004 0.003 0.01 0.011
(0.010) (0.011) (0.009) (0.010)
BaselineContols? N Y N Y
Rsquared 0.02 0.02 0.00 0.00
0.022 0.022 0.004 0.004
(0.012) (0.012) (0.011) (0.011)
0.020 0.021 0.029* 0.030**
(0.013) (0.017) (0.014) (0.015)
BaselineContols? N Y N Y
Rsquared 0.03 0.03 0.01 0.01
Meandependentvariable 0.035 0.035 0.026 0.026
Observations 2,734 2,734 1,019 1,019
*** t i ifi t th 10 5 d 1 % ti l
WomenLevel HouseholdLevel
N.Obs All T T
Receivedvisitandinformationbeforeelections(1=Yes) 2,637 0.71 1.00 1.00 1.00 0.00 0.00 0.00 0.00
Neighborsjoinedduringvisit(1=Yes) 1,867 0.11 0.11 0.08 0.15
Importanceofvoting 1,867 0.64 0.64 0.98 0.19
Ballotingprocessandsecrecyofballot 1,867 0.06 0.06 0.02 0.12
Both 1,867 0.30 0.30 0.01 0.69
Discussedvisitwithneighbors(1=Yes) 1,867 0.41 0.41 0.35 0.50
Discusspoliticalissueswithwomeninneighborhood(1=Yes) 2,637 0.44 0.55 0.50 0.62 0.40 0.30 0.51 0.18
Party/CandidatePositions 847 0.61 0.62 0.61 0.63 0.59 0.58 0.61 0.59
Importanceofvoting 847 0.86 0.85 0.85 0.86 0.86 0.89 0.83 0.88
Importanceofvotinginaccordancetoownpreferences 847 0.52 0.53 0.53 0.53 0.47 0.49 0.45 0.51
p g p
Votedforthesamepartyasmalehead 44.6 41.7 0.500 13.5 11.6 0.326 57.25 56.94 0.950
Votedfordifferentpartyfromhead 10.1 2.8 0.010 2.2 1.4 0.647 13.15 3.47 0.000
Votedbutmaleheaddidnot 6.1 3.7 0.220 1.7 2.7 0.274 7.89 4.17 0.090
Didnotvote 38.6 50.9 0.010 82.0 84.2 0.526 21.04 34.03 0.010
N.Observations 1,870 434 539 146 1,331 288
AllWomen Notvotedinthepast Votedinthepast