metadata: authors: 0: author: Gine, Xavier
1: author: Mansuri, Ghazala
count: Pakistan
docna: 0: docna: Together we will : experimental evidence on
            female voting behavior in Pakistan
docty: Policy Research Working Paper
subtopic: Conflict and Fragile States,Social Analysis,Gender and Development,Inequality,Natural Disasters
teratopic: Agriculture,Gender,Governance,Health, Nutrition and Population
abstracts: cdata!: In many emerging democracies women are
            less likely to vote than men and, when they do vote, are
            more likely to follow the wishes of household males. The
            authors assess the impact of a voter awareness campaign on
            female turnout and candidate choice. Geographic clusters
            within villages were randomly assigned to treatment or
            control, and within treated clusters, some households were
            left untreated. Compared with women in control clusters,
            both treated and untreated women in treated clusters are 12
            percentage points more likely to vote, and are also more
            likely to exercise independence in candidate choice,
            indicating large spillovers. Data from polling stations
            suggest that treating 10 women increased turnout by about 9
            votes, resulting in a cost per vote of US$ 2.3. Finally, a
            10 percent increase in the share of treated women at the
            polling station led to a 6 percent decrease in the share of
            votes of the winning party.
geo_reg_key: 80475,80451,80470
repnme: repnme: Together we will : experimental evidence on
            female voting behavior in Pakistan
display_title: Together we will : experimental
            evidence on female voting behavior in Pakistan
listing_relative_url: /research/2011/06/14410576/together-experimental-evidence-female-voting-behavior-pakistan
topicv3: Poverty m1326687 695,Political Participation m1327389 926,Gender m1327621 615,Landslide m1503664 3204,Military m1505651 3036
publishtoextweb_dt: 2010-07-01T00:00:00Z
historic_topic: Agriculture,Gender,Governance,Health, Nutrition and Population
no_of_pages: 52
model_extractions: WPS5692 Policy Research Working Paper 5692

# Together We Will

Experimental Evidence on Female Voting Behavior in Pakistan _Xavier Giné Ghazala Mansuri_ The World Bank Development Research Group Finance and Private Sector Development Team & Poverty Reduction and Economic Management Network Poverty Reduction and Equity June 2011
Policy Research Working Paper 5692

# **Abstract**

In many emerging democracies women are less likely to vote than men and, when they do vote, are more likely to follow the wishes of household males. The authors assess the impact of a voter awareness campaign on female turnout and candidate choice. Geographic clusters within villages were randomly assigned to treatment or control, and within treated clusters, some households were left untreated. Compared with women in control clusters, both treated and untreated women in treated clusters are 12 percentage points more likely to vote, and are also more likely to exercise independence in candidate choice, indicating large spillovers. Data from polling stations suggest that treating 10 women increased turnout by about 9 votes, resulting in a cost per vote of US$ 2.3. Finally, a 10 percent increase in the share of treated women at the polling station led to a 6 percent decrease in the share of votes of the winning party.

This paper is a product of the Finance and Private Sector Development Team, Development Research Group; and the Poverty Reduction and Equity Team, Poverty Reduction and Economic Management Network. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at xgine@worldbank.org and gmansuri@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# **Together We Will: Experimental Evidence on Female Voting Behavior in Pakistan**

Xavier Giné and Ghazala Mansuri<sup></sup> JEL: D72, P16, 012 Keyword: externalities, information campaign, voting behavior, elections, field experiment Giné: Development Research Group, The World Bank (e-mail:xgine@worldbank.org). Mansuri: Development Research Group, The World Bank (e-mail: gmansuri@worldbank.org). 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 Martínez-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 world‘s 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<sup>th</sup> century and the new democracies that emerged after WWII followed suit and granted women _de jure_ rights to political participation in all democratic institutions.<sup>1</sup> 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).<sup>2</sup> While women‘s relative absence from elected public office has received considerable policy attention in recent years<sup>3</sup> , there have been few attempts to reduce barriers to women‘s 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 concerns.<sup>4</sup>

> 1  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).

> 2 See also Zia and Bari (1999) and Bari (2005) for Pakistan.

> 3 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.

> 4 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 women‘s 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.

2
Women in emerging democracies may face two distinct barriers to exercising their right to vote for a candidate of their choice. 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 poorer sources of information about the significance of political participation or the balloting process, perhaps due in part to illiteracy and limited mobility. Lack of information may also reinforce stereotypes that further disengage women from public life.

However, while attitudes and social mores change slowly, information provision can occur relatively quickly.<sup>5</sup> 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. At the same time, the mere act of participation may also serve to weaken pejorative perceptions about female efficacy that limit women‘s engagement in public life (Beaman et al., 2007).

We test these ideas by conducting a field experiment to assess the impact of information 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).<sup>6</sup> The awareness campaign was conducted just before the 2008 national elections. Study villages were divided into geographical clusters which were randomly assigned to treatment or control. Within treated clusters, only a _subset_ of sample households was randomly assigned to receive a door-to-door awareness campaign. This allows us to assess the magnitude of spillovers within treated clusters without confronting the usual set of identification problems (Manski, 1993; 1995).

> 5 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).

> 6 Zia and Bari report that women's registration as voters is often considered neither necessary nor appropriate by either household males or political parties. They also note that, in addition to cultural restrictions on mobility and low levels of literacy, women's lack of knowledge about the electoral system and about voting procedures constitutes an important barrier to the registration of women and female turnout in elections (pg. 89).

3
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 the first and the second, allowing us to test whether the knowledge that ballots are cast in an environment of secrecy enhances female participation, as well as 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 treated women and their untreated close neighbors, 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.

We also use administrative data from all polling stations that served the study villages and 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 electoral participation and processes is less salient for men or that there is little communication about political matters between men and women. Of course, it is also possible that men are simply not influenced by information provided by women.

We then study 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 for political party. Control women in treated clusters behaved again as if directly treated, confirming once more the importance of social interactions. Polling station data show as well that an increase of 10 percent in the share of treated women led to 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, had it been implemented at a larger scale.

4
Given this result, we next check whether treatment decreases the male head‘s knowledge of the candidate choice of women in his household. Using follow-up survey data which 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, we construct cross-reports regarding candidate choice. Using these cross-reports, we find that male heads in treated households 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 control clusters, among whom turnout was lower, were less likely to believe that the election was free and fair and more likely to report witnessing or hearing instances of violence in the village, compared to reports by women in treated clusters.

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 and institutionalized party structures are also much less developed (Aker et al. 2010, Banerjee et al. 2010 and Pande 2011 for a review).<sup>7,8</sup> This paper contributes, therefore to two literatures. First, it adds to this nascent literature on preelection voter information campaigns in developing countries. Second, it is the only paper which, to our knowledge, assesses the impact of information externalities on voter turnout and candidate choice. This is critical for correctly measuring the cost-effectiveness of an information campaign, but it is also important for assessing the types of information that can be successfully transmitted through social networks.<sup>,</sup> In this regard, our paper is closest to Duflo and Saez (2003) and contributes also to the burgeoning literature on social networks and peer effects (e.g. Sacerdote, 2000 and Kling, Liebman and Katz, 2007).

> 7 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. Perhaps more related to our study, Nickerson (2008) conducted a door-to-door canvassing experiment to assess information spillovers within the household. He targets households with two registered voters and finds that the member that did not answer the door is nearly 60% as likely to vote as the treated member.

> 8 In developing countries there is a small experimental literature that has focused on electoral violence, clientelism and vote buying in the context of developing countries. Collier and Vicente (2007), for example, study the effect of an information campaign against electoral violence in Nigeria. Wantchekon (2003) has examined the effectiveness of clientelist messages in Benin and Vicente (2007) analyzes an information campaign against vote buying in Sao Tome and Principe, Vicente and Wantchekon (2009) provides a review.

5
While peer pressure may have contributed to the increase in turnout we observe (Funk, 2010), we provide evidence suggesting that the information content of the campaign mattered. First, 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 one‘s own preferences. Second, male heads of control households in clusters treated with the message about the secrecy of the balloting process are less informed about the candidates chosen by women in their household, compared to control households in clusters treated with the message about the importance of voting only. This is evidence that even the more nuanced message about the secrecy of voting was conveyed to control women in treated clusters.<sup>910</sup> 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

> 9 In this sense the awareness campaign studied here is quite different from most GOTV campaigns, whose objective is to increase turnout by persuading subjects to vote. The awareness campaign, in contrast, is designed to inform women about their rights in the electoral process and how to exercise them .

> 10 One could also argue that the increase in turnout was due to the mere salience of the campaign (e.g. Zwane et al. forthcoming). 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.  In addition, one could argue that the mere visit could have motivated treated women to vote (if they felt special for having been chosen and voted out of reciprocity). This is unlikely because untreated women in treated clusters (not chosen to receive the visit) show comparable turnout rates to directly treated women.

6
microfinance to its partner organizations, which are mostly NGOs. MRDO is one such nonpartisan NGO funded primarily by PPAF, that mobilizes women using a community based approach. 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 Sindh. The districts were selected because of sharp electoral competition between the two main political parties, the Pakistan People‘s 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 initial sample included 12 villages, 6 villages from each district, and 24 polling stations from two constituencies.<sup>11</sup> 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.

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<sup>th</sup> , 2008, the elections were postponed to February 18<sup>th</sup> , 2008 because Benazir Bhutto,

> 11 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 (see http://www.ecp.gov.pk/ for more information).

7
the leader of the PPPP, and a twice elected Prime Minister, was assassinated on December 27<sup>th</sup> , 2007.

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 Bhutto‘s assassination and the increased visibility of 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.<sup>12</sup> 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 (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). The information campaign never mentioned a political party or candidate by name. As mentioned, this also distinguishes our awareness campaign from a GOTV campaign.<sup>13</sup> Appendix A contains the translation of the script and Appendix B the translated visual aids.

> 12 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 women‘s 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.

> 13 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.

8
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 is critical to measuring information spillovers and the cost-effectiveness of the campaign. Second, door-to-door information campaigns in the US have proven more cost-effective than other strategies like phone calls and direct mailings.<sup>14</sup> 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.<sup>15</sup> 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 rather 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.<sup>16</sup> 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

> 14 Gerber and Green (2000a) reports 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. 15 See Jacoby and Mansuri (2011)

> 16 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.

9
engage, women tend to avoid formal authority and reach out to traditional or religious leaders (66 percent among women compared to 49 among men).<sup>17</sup>

# **2.2 Experimental Design and Data**

The timeline of the study is shown in Figure 1. The information campaign was carried out two weeks prior to the elections (from February 5<sup>th</sup> to 15<sup>th</sup> 2008) by 8 teams consisting of one MRDO female staff and one female enumerator from RCONs each.<sup>18</sup> Each sample village was covered in approximately one day and was divided into contiguous geographical clusters of approximately 40 households. A cluster was typically one or two contiguous streets in the village. Clusters were based on geography rather than other household characteristics such as caste or occupation of household head because restrictions to female mobility suggested that social interactions would be dictated by physical proximity. Each cluster was then randomly assigned to receive the importance of voting message (T1), or T1 plus the secrecy of balloting message (T2) or nothing. The canvassing team selected one cluster in each village at random and began there. T1 was delivered in this cluster. Next, a gap cluster was left between two selected clusters. In the second selected cluster a coin toss determined whether T2 was delivered or all selected households were left as controls. The third selected cluster was then given the opposite treatment of the second cluster. 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 T1, 27 assigned to T2 and 10 left as controls.<sup>19</sup> Within each selected cluster, irrespective of the specific treatment, every 4<sup>th</sup> household was selected and surveyed, starting at either end of the cluster. In T1 and T2 clusters, all selected households were assigned to the respective treatment, with the exception of every 5<sup>th</sup> selected household which was left as a

> 17 These statistics are also consistent with Pakistan‘s 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).

> 18 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.

> 19 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.

10
control. This generated 2 to 4 controls in each T1 and T2 cluster in addition to the households selected in the control clusters. Thus, similar to Duflo and Saez (2003), 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 maps a section of a study village containing three clusters delimited by a white solid line. 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 T1 (T2) cluster and a triangle is a control household in a treated cluster (either T1 or T2). 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. None of the households refused to participate in the awareness campaign or to be interviewed.

A local woman, usually a school teacher, was also identified in each village during the awareness campaign to assist the canvassing team with the verification of voting, post-election, by checking the ink stain on each woman‘s hand. This woman was provided the list of sample women whose thumb mark needed 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 head‘s 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<sup>th</sup> , Election Day, and the evening of February 19<sup>th</sup> . The field teams visited each village on February 19<sup>th</sup> to check 10 percent of the verifier‘s assignment at random and found no significant differences.

11
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 of women was unrelated to treatment assignment (see Appendix Table A3), although we note that T2 households are more likely to attrit. Since the overall household attrition rate is very low (2.6 percent), this is not a source of concern. 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 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 which served our sample villages.<sup>20</sup> 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 (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 T1 and T2 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

> 20 Results by gender are tabulated at each polling station. This is possible because in Pakistan polling areas and polling booths are separated by gender.

12
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. In the analysis we control for all household and woman characteristics that lack balance across treatment and control groups.

Appendix Table A4 suggests that the intervention was successfully implemented: all treated women correctly recall having received a visit and none of the control households do. In addition, most treated women correctly recall the content of the messages delivered. 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 one‘s 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 villages.<sup>21</sup> 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) travelled on foot, a substantial number (26 percent) used transportation provided by a political party, which is legal in Pakistan. However, almost all women went to the polling station with others. The majority were accompanied by female household members (62 percent), or a female friend or relative (25 percent). The rest went with their spouses or another household male.

> 21  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).

13
# **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 via the following OLS regression equation: where indicates whether woman _i_ in household _h_ in cluster _c_ in polling station _p_ in village _v_ is verified as having voted (1=Yes), 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‖.<sup>22</sup> Finally, we include in the total number of women registered to vote in the polling station. Inclusion of corrects for baseline imbalances and increases efficiency by absorbing residual variation in the data.<sup>23</sup> We also include a village fixed effect to remove the influence of village specific unobservable characteristics. The term 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 Equation (1) measures the effect of T1 and T2 separately: The coefficients capture the impact of treatment on turnout and are the main coefficients of interest.

> 22 Although the NIC is required to vote, some women in our sample were verified as having voted, though they did not have an NIC. 23 Some of the variables were collected at baseline, prior to the campaign, while others were collected in the follow up survey. In either case, they are not characteristics that could be affected by the campaign.

14
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 TN-CN). Here treated and control women in treated households are grouped together. In column 3, we compare treated women in treated clusters with women in control clusters (comparison T-CN). 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 CTN-CN). If spillover effects are important, the coefficient of interest in the first (naïve) comparison should be smaller since control women in treated clusters are likely to have been influenced by treated women.

We indeed find that the naïve estimate in column 1, panel A, is lower than that of columns 2-4, at 6 percent. Thus, accounting for within geographical cluster spillovers increases the impact of treatment to about 12 percent. More importantly, control women in treated clusters are about as likely to vote as directly treated women.<sup>24</sup> 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 T2 are larger. They are also more precisely estimated, although we are unable to detect statistically different effects between T1 and T2.<sup>25</sup> 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

> 24 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.

> 25 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.

15
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 equation: Where 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 is the total number of surveyed households within distance radius _d_ of household _h_ .<sup>26</sup> 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<sup>th</sup> , 50<sup>th</sup> and 75<sup>th</sup> 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 . 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 percent. The estimate of 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 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

> 26 It is clear that the dummies and cannot both take value 1, since households are either treated or not. Both dummies take value zero if the household was not treated ( ) and was located more than _d_ meters from the closest treated household.

16
OLS regression equation analogous to Equation (2). We again find that the direct (and indirect) effect of T2 is somewhat larger than that of T1 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 of the cluster level randomization.<sup>27</sup> 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 0-200 meters and extend up to 1,200 meters. The regression specification in this case is Where is the number of treated women between distance _d_ and _D_ from each sample woman, and 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 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 percent and a median increase of 45 percent.<sup>28</sup> 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. ). Clearly, social interactions among women with mobility constraints are largely

> 27 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.

> 28 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 ( 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.

17
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 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, , 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.<sup>29</sup> We include a vector of polling station level variables, to control for polling station level differences. This yields the following regression specification: 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 percent, depending on whether polling station controls are included. This provides further confirmation of the size and significance of the spillover effects we find in Table 5.<sup>30</sup> 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 men‘s greater exposure to political information, wider networks or simply lack of effective communication between men and women on political issues.

# **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. As before, the estimates in column 1 compare treated households to control

> 29 The variable ranges from 0 to 0.77. 30 Note that the results from Table 5 indicate that spillover effects are significant up to one kilometer, on average. 18
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 percentage points. In Panel B, the impacts for T2 are again larger in absolute value and more precisely estimated than those of T1, 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 led 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 pro-women in any way.

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 possessed 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 reporter‘s 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.<sup>31</sup> Candidate choice information is available for all women who

> 31 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 don‘t 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 woman‘s voting behavior could reflect either indifference or freedom to select whomever she

19
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.<sup>32</sup> 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 women in the household. We test this with the following regression (6) where is an indicator that takes the value 1 if the report of individual _i_ on individual _j_ ‘s choice of candidate is correct (according to _j_ ‘s self-report); is an indicator for whether reporter _i_ is the male head; and is reporter _i_ ‘s 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 women‘s chosen candidates by about 8 percentage points. As before, effects are larger and measured more precisely for T2. 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 T2 are significantly different from T1 ( _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

> 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. 32 Among the 2,637 women in the sample, 1,543 were verified as having voted. The discrepancy in sample sizes of voters come from 21 percent of women that were verified as having voted but self-reported as not having done so. 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). This is especially true in more contested polling stations

> (45.3 percent vs. 35.8 percent, _p-value=_ 0.000).

20
women. This confirms the importance of the information provided in the campaign. Even the more nuanced message about the secrecy of the ballot was apparently conveyed to women not directly treated.

Table A5 complements these results by comparing the turnout and candidate choice of treated women with women in control clusters.<sup>33</sup> Columns 1 and 2 suggest that treated women are more likely to vote and to do so precisely for a party (candidate) other than that of the male head (from 2.8 to 10.1 percent). 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.

Apparently, 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. Since 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 women‘s 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 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.

> 33 The results are very similar when comparing treated clusters versus control clusters or controls in treated clusters versus control clusters and hence are omitted.

21
The results suggest 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 prodemocratic views. Interestingly, columns 5-6 provide strong evidence of cognitive dissonance in voting. Women in control clusters were less likely to report that elections were free and fair and 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 delegitimizing the election process and 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 twothirds 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 cost—which 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).<sup>34</sup> 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

> 34 This is about Rs. 201 (Rs. 453 including fixed costs), using the exchange rate in February 2008.

22
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).<sup>35</sup>

# **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 percent 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.

> 35 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.

23
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 alters the cost benefit analysis quite substantially. An additional vote costs more than seven times as much as it does in the absence of spillovers. Given the relatively low cost of an additional vote ($2.3, using variable costs only), information campaigns appear to be a relatively cost effective way of increasing turnout among poor rural women.

While voter awareness campaigns are a staple feature of developed democracies they are relatively rare in younger and emerging democracies and we are not aware of any other studies that systematically examine the prospects of such interventions for increasing women‘s engagement in public life in a developing country context. Arguably, though, the value of information is likely to be greater in a context where voters have less knowledge about the policy positions taken by candidates or parties and are engaged in various clientelist relationships that influence voting decisions. Access to reliable information is likely to be an even greater barrier for women, who are generally more constrained by lack of education, lower levels of mobility and less exposure to public spaces in which political ideas can be developed.

# **Bibliography**

Aker, Jenny, Paul Collier and Pedro Vicente, 2010, Voter Education Using Cell Phones: Evidence from a Field Experiment in Mozambique, mimeo.

Alesina, Alberto, Paola Giuliano and Nathan Nunn, 2010, The Origins of Gender Roles: Women and the Plough, mimeo.

24
Alesina, Alberto and Paola Giuliano, 2010, The power of the family. Journal of Economic Growth, 15(2):93–125.

Associated Press, Feb 18<sup>th</sup> , 2008, ―Some Pakistani Women Warded Off Voting‖.

Banerjee, Abhijit V., Selvan Kumar, Rohini Pande and Felix Su, 2010, ―Do Informed Voters Make Better Choices? Experimental Evidence from Urban India‖, mimeo.

Bari, Farzana, 2005, ―Women‘s Political Participation: Issues and Challenges‖, prepared for the Expert Group Meeting on Enhancing Participation of Women in Development through an Enabling Environment for Achieving Gender Equality and the Advancement of Women, United Nations.

Beaman, Lori, Raghabendra Chattopadhyay, Esther Duflo, Rohini Pande, and Petia Topalova, 2009, ―Powerful Women: Does Exposure Reduce Prejudice?", _Quarterly Journal of Economics_ Bratton, Michael, 2008, ―Voting Buying and Violence in Nigerian Election Campaigns.‖ Afrobarometer Working Paper No. 99.

Bruhn, Miriam, and David McKenzie. 2009. "In Pursuit of Balance: Randomization in Practice in Development Field Experiments." _American Economic Journal: Applied Economics_ , 1(4): 200–232.

Cardy, Emily A, 2005, ―An Experimental Field Study of the GOTV and Persuasion Effects of Partisan Direct Mail and Phone Calls.‖ _Annals of the American Academy of Political and Social Science_ 601: 28–40.

Chattopadhyay, Raghabendra, and Esther Duflo, 2004, ―Women as Policy Makers: Evidence from a Randomized Policy Experiment in India," _Econometrica_ , 72(5): 1409-1443.

Cialdini, Robert B., and Noah J. Goldstein, 2004, ―Social Influence: Compliance and Conformity.‖ _Annual Review of Psychology_ 55: 591–621.

CLRAE (Council of Europe‘s Parliamentary Assembly and Congress of Local and Regional Authorities of Europe), 2002, _Women’s individual voting rights: a democratic requirement_ . Council of Europe Publishing.

Collier, Paul and Pedro C. Vincente, 2008, ―Votes and Violence: Evidence from a Field Experiment in Nigeria.‖ University of Oxford, Working Paper.

Croson, Rachel and Uri Gneezy, 2009, Gender Differences in Preferences, _Journal of Economic Literature_ , Volume 47, Number 2, Pages 448-474.

Downs, Anthony. 1957. _An Economic Theory of Democracy_ . New York: Harper and Row.

25
Duflo, Esther and Emmanuel Saez, 2003, The Role of Information and Social Interactions in Retirement Plan Decisions: Evidence From a Randomized Experiment, _Quarterly Journal of Economics_ , Vol. 118, No. 3, Pages 815-842.

Edlund, Lena and Rohini Pande, 2002, ̳Why have Women Become Left-Wing? The Political Gender Gap and the Decline in Marriage‘, _Quarterly Journal of Economics_ , Vol. 117, No. 3, Pages 917-961.

Fafchamps, M. and F. Gubert, 2006, ―The formation of risk sharing networks‖, _Journal of Development Economics_ , 83(2):326-350.

Fernandez, Raquel. 2007. Women, work and culture. _Journal of the European Economic Association_ , 5(2–3):305–332.

Fernandez, Raquel and Alessandra Fogli. 2009. ―Culture: An empirical investigation of beliefs, work, and fertility.‖ _American Economic Journal: Macroeconomics_ 1(1):146–177.

Fortin, Nicole. 2005. ―Gender role attitudes and the labour market outcomes of women across oecd countries.‖ _Oxford Review of Economic Policy_ 21:416–438.

Funk, Patricia. 2010. ― Social Incentives and Voter Turnout: Evidence from the Swiss Mail Ballot System ‖, _Journal of the European Economic Association_ 8(5): 1077–1103.

Hoddinott, John and Haddad, Lawrence, 1995, Does female income share influence household expenditures? Evidence from Cote D‘Ivoire, Oxford Bulletin of Economics and Statistics, vol. 57(1), pp. 77–95.

Gerber, Alan S., and Donald P. Green, 2000a, ―The Effects of Canvassing, Telephone Calls, and Direct Mail on Voter Turnout: A Field Experiment.‖ _American Political Science Review_ 94(3): 653–63.

Gerber, Alan S., and Donald P. Green. 2000b. ―The Effect of a Nonpartisan Get-Out-the-Vote Drive: An Experimental Study of Leafletting.‖ _Journal of Politics_ 62(3):846-857.

Gerber, Alan S., and Donald P. Green. 2001. ―Do Phone Calls Increase Voter Turnout?: A Field Experiment.‖ _Public Opinion Quarterly_ 65(1):75-85.

Gerber, Alan S., and Donald P. Green. 2004. ―Get Out the Vote: How to Increase Voter Turnout‖ Brookings Institution Press: Washington, DC.

Gerber, Alan S., and Donald P. Green. 2005. ―Do Phone Calls Increase Voter Turnout? An Update.‖ _Annals of the American Academy of Political and Social Science_ 601: 142-154.

26
Gerber, Alan S., Donald P. Green, and Ron Shachar. 2003. ―Voting May Be Habit-Forming: Evidence from a Randomized Field Experiment.‖ _American Journal of Political Science_ 47 (3): 540–50.

Green, Donald P., Alan S. Gerber, and David W. Nickerson. 2003. ―Getting Out the Vote in Local Elections: Results from Six Door-to-Door Canvassing Experiments.‖ _Journal of Politics_ 65 (4): 1083–96.

Gerber, Alan S., Donald P. Green and Christopher W. Larimer. 2008. ―Social Pressure and Voter Turnout: Evidence from a Large-scale Field Experiment.‖ _American Political Science Review_ 102 (1): 33-48.

Harbaugh, W. T. 1996. ―If People Vote because they Like to, then Why do so Many of them Lie?‖ Public Choice 89 (October):63–76.

Horiuchi, Yusaku, Kosuke Imai and Naoko Taniguchi. 2007. ―Designing and analyzing randomized experiments: application to a Japanese election survey experiment.‖ _American Journal of Political Science._ 51(3):669–687.

Imai, Kosuke. 2005. "Do Get-Out-the-Vote Calls Reduce Turnout? The Importance of Statistical Methods for Field Experiments." American Political Science Review, 99 (2): 283-300.

Jacoby, Hanan and Ghazala Mansuri, 2011, ―Crossing Boundaries: Gender, Caste and Schooling in Rural Pakistan‖, mimeo Kling, Jeffrey, Jeffrey Liebman, and Larry Katz. 2007. ―Experimental Analysis of Neighborhood Effects‖ _Econometrica_ , 75 (1): 83-119.

Krackhardt, David. 1988. ―Predicting with Networks: Nonparametric Multiple Regression Analysis of Dyadic Data.‖ _Social Networks_ , 10(4): 359–81.

Kremer, Michael and Edward Miguel, 2001, ―Worms: Identifying Impacts On Education And Health In The Presence Of Treatment Externalities,‖ _Econometrica_ , Vol. 72, No. 1, 159–217 Lott, John R. Jr. and Lawrence W. Kenny. 1999. ―Did Women‘s Suffrage Change the Size and Scope of Government?‖ _Journal of Political Economy_ 10 (Dec.): 1163-1198.

Lundberg, Shelly, Pollak, Robert and Wales, Terence, 1997, Do husbands and wives pool their resource? Evidence from the United Kingdom child benefit. Journal of Human Resources, vol. 32(3), pp. 463–80.

Manski, Charles F. 1993. "Identification of endogenous social effects: the reflection problem," _Review of Economic Studies_ 60:531-542 Manski, Charles F. 1995. Identification Problems in the Social Sciences. Harvard University Press, Cambridge).

27
Michelson, Melissa R. 2003. "Getting Out the Latino Vote: How Door-to-Door Canvassing Influences Voter Turnout in Rural Central California." _Political Behavior_ 25(3): 247-63.

Michelson, Melissa R. 2005. ―Meeting the Challenge of Latino Voter Mobilization‖ _Annals of the American Academy of Political and Social Science_ , 601 (September): 85–101.

Milbrath, Lester W. 1965. Political Participation: How and Why Do People Get Involved in Politics? Chicago: Rand McNally.

Moulton, Brent R. 1986. ̳ ̳Random Group Effects and the Precision of Regression Estimates,‘‘ _Journal of Econometrics_ 32: 385–397.

Mullainathan, S. and E. Washington. 2009. ―Sticking with Your Vote: Cognitive Dissonance and Political Attitudes‖ _American Economic Journal: Applied Economics_ , 1, 1, 86-111.

Nickerson, David W. 2006. ―Volunteer Phone Calls Can Increase Turnout: Evidence from Eight Field Experiments.‖ American Politics Research 34 (May): 271–92.

Nickerson, David W. "Friends Don't Make Friends Vote: Selection and Reputation in Voter Mobilization" Paper presented at the annual meeting of the American Political Science Association, Hyatt Regency Chicago and the Sheraton Chicago Hotel and Towers, Chicago, IL, Aug 30, 2007.

Nickerson, David W. 2008. ―Is Voting Contagious? Evidence from Two Field Experiments.‖ American Political Science Review, 102(1): 49–57.

Plutzer, Eric. 2002. ―Becoming a Habitual Voter: Inertia, Resources, and Growth in Young Adulthood.‖ American Political Science Review 96(2): 41–56.

Riker, William H., and Peter C. Ordershook. 1968. ―A Theory of the Calculus of Voting.‖ _American Political Science Review_ 62:25-43.

Sacerdote, Bruce, 2001, ―Peer Effects with Random Assignment: Results for Dartmouth Roommates," _Quarterly Journal of Economics_ , 116(2), 681-704.

Thomas, Duncan, 1990, Intra-Household Resource Allocation: An Inferential Approach The Journal of Human Resources, Vol. 25, No. 4: pp. 635-664 Vicente, Pedro C. 2007. ― _Is_ Vote Buying Effective? Evidence from a Field Experiment in West Africa.‖ Oxford University and BREAD, Working Paper.

Vicente, Pedro C. and Leonard Wantchekon, 2009, Clientelism and vote buying: lessons from field experiments in African elections, Oxford Review of Economic Policy, Volume 25, Number 2, 2009, pp.292–305 28
Wantchekon, Leonard. 2003. ―Clientelism and Voting Behavior: Evidence from a Field Experiment in Benin.‖ _World Politics_ 55(2):399-422.

Zia, Shahla and Farzana Bari, 1999, Baseline Report on Women's Participation in Political and Public Life in Pakistan, Aurat Publication and Information Service Foundation and the International Women's Rights Action Watch - Asia Pacific (IWRAW). Crystal Publishers, Blue Area, Islamabad.

Zwane, A. J. Zinman, E Van Dusen, W. Pariente, C. Null, E. Miguel, M. Kremer, A. Karlan, R. Hornbeck, X. Giné, E. Duflo, F. Devoto, B. Crepon, A. Banerjee. Forthcoming. ―Risk of asking: Being surveyed can affect later behavior.‖ _Proceedings to the National Academy of Sciences_ .

29
# **Appendix A: Visit Script**

## **<u>Importance of Voting (T1)</u>**

**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 member’s 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 candidate?

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

30
sincere people would also contest elections and we would vote for them because of their genuine attributes. (Just as shown in **Picture 7** ).

# **<u>Secrecy of Balloting (T2)</u>**

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!

31
<!-- Start of picture text --> q Se wihlnnsize Zt<br>B \aZZwe<br>Ly <- = Ve<br>eee<br><!-- End of picture text --> <!-- Start of picture text --> s ptt 5<br>eI yopognS Kloof<br><!-- End of picture text --> <!-- Start of picture text --> ,<br>&) ei SUF ISIw<br>= 1<br>ha a Zt / fs Soe RON Zee ay<br>ae iy am =ory<br><!-- End of picture text --> <!-- Start of picture text --> 2 WBitfinzeinl 1<br>@ ame @<br>“s/<br>5 i a | | om<br><!-- End of picture text -->

<!-- Start of picture text --> = , ily oe yy a<br>| Pa 6<br>tat tages<br><!-- End of picture text -->

<!-- Start of picture text --> 6 babes SF| IGL?rd<br>ir S—<br>& ae<br>Tis fess. <<)<br><!-- End of picture text -->
<!-- Start of picture text --> uv op fata<br>algpete|oy ey) | eee5, S|| ASA|Bae)| ysRM I<br>= a =<br><!-- End of picture text -->

<!-- Start of picture text --> has = ens | — =<br><!-- End of picture text -->

<!-- Start of picture text --> —_ gethewte Mer<br>SS —e—=S<br>- Tioprem ZLG ee<br>=e & Ne<br>a wal VA i Lo a4 M<br>/ oy Ni] AL) A if )<br><!-- End of picture text --> <!-- Start of picture text --> / oy Ni] AL) A if )<br><!-- End of picture text --> <!-- Start of picture text --> SS<br>he<br>ron<br><!-- End of picture text -->
<!-- Start of picture text --> Labi CLs<br>_<br>=<br><!-- End of picture text --> <!-- Start of picture text --> Ue a Keb MbequtlaelCdrd<br>( = 3 = 2 4<br>% |€| 2<br>( 6 5 = 4<br>& By<br><!-- End of picture text -->

<!-- Start of picture text --> 83 wn (bya Les<br>Fi by cts ibys,<br>IS id) Oe<br>Migtig> — ECigs<br>ye te fe \<br>WA i nt te<br><!-- End of picture text -->
**Figure 2: Section of Village with geographical clusters**

Notes: The solid white lines delimit a geographical cluster. A square represents the location of a T1 household, a star represents a T2 household and a dot represents a control household in a control cluster. A triangle represents a control household in a treated cluster (either T1 or T2).

35
|Table 1: SummaryS|tatistics||||||
|---|---|---|---|---|---|---|
||N. Obs|Mean|St. Dev|Pct 10|Pct. 50|Pct. 90|
|Panel A: Polling Station Characteristics|||||||
|Number of women registered in each polling station|21|434.0|196.7|195.0|464.0|656.0|
|Number of treated women in each polling station|21|89.0|54.2|34.0|82.0|150.0|
|Share of treated women|21|0.24|0.19|0.07|0.22|0.43|
|Turnout for women|21|0.58|0.27|0.30|0.54|0.91|
|Turnout for men|21|0.49|0.15|0.32|0.51|0.66|
|Share of PPPP among female voters|21|0.62|0.26|0.39|0.66|0.88|
|Share PPPP among male voters|21|0.63|0.25|0.33|0.67|0.93|
|Percentage of women with access to cable in the polling station|21|0.34|0.26|0.06|0.23|0.75|
|St. Dev of asset index|21|1.76|0.30|1.46|1.72|2.09|
|St. Dev of distance index|21|0.79|0.52|0.16|0.69|1.31|
|Panel B: Household Characteristics|||||||
|Household size|963|10.2|5.17|5|9|16|
|Number of women in the household<sup>1</sup>|991|2.69|1.48|1|2|5|
|Asset Index|963|0.00|1.85|-2.03|-0.49|2.66|
|Total owned land (in acres)|963|2.58|7.55|0.01|0.04|7.02|
|Average monthly expenditure (in Rs. thousands)|963|8.80|4.71|3.00|9.00|12.50|
|House quality index|963|0.00|1.38|-1.62|-0.32|1.97|
|Low Zaat Status|963|0.26|0.44|0|0|1|
|Received visit from political party staff prior to election (1=Yes)|963|0.75|0.43|0|1|1|
|Attended political rally before intervention (1=Yes)|963|0.24|0.43|0|0|1|
|Distance to polling station (Km.)<sup>1</sup>|991|0.97|0.91|0|1|2|
|Distance between households within geographical cluster (meters)|8,263|194.2|283.9|27.9|107.1|456.5|
|Distance between households within village(meters)|48,430|1,472.9|1,304.9|109.4|1,070.5|2,962.8|
|Panel C: Woman Characteristics|||||||
|Age|2,637|37.76|16.09|20|35|60|
|Woman has formal schooling (1=Yes)|2,637|0.18|0.39|0|0|1|
|Attended political rally before intervention (1=Yes)|2,637|0.80|0.40|0|1|1|
|Number of children under 5 years old|2,637|0.86|1.19|0|0|3|
|Woman has a National Identity Card (NIC or CNIC) (1=Yes)|2,637|0.70|0.46|0|1|1|
|Woman voted in last local elections (1=Yes)<sup>1</sup>|2,735|0.70|0.46|0|1|1|
|Access to radio (1=Yes)|2,637|0.48|0.50|0|0|1|
|Access to TV (1=Yes)|2,637|0.70|0.46|0|1|1|
|Access to cable (1=Yes)|2,637|0.30|0.46|0|0|1|
|Mobility Index (0 to 3)|2,637|2.17|0.42|2|2|3|
|Woman allowed to join an NGO (1=Yes)|2,637|0.73|0.44|0|1|1|
|Woman is a member of MRDO (1=Yes)<sup>1</sup>|2,735|0.11|0.31|0|0|1|
|Woman seeks advice from a religious leader or "Pir"(1=Yes)|2,637|0.64|0.48|0|1|1|

Notes:<sup>1</sup> indicates that the variable is created using only the sample from the pre-election visit. Variables are defined in Appendix Table A1.
Table 2: Differences by treatment status

||Treatment vs<br>control households|Treatment 1 vs<br>control<br>households|Treatment 2 vs<br>control<br>households|Treated<br>clusters vs<br>control cluster|s<br>Treated<br>households vs<br>households in<br>control clusters|<br> <br> <br>Control households<br>in treated clusters<br>vs households in<br>control clusters|
|---|---|---|---|---|---|---|
||T-C|T1-C|T2-C|TN-CN|T-CN|CTN-CN|
||(1)|(2)|(3)|(4)|(5)|(6)|
|Panel A: Household Characteristics|||||||
|Household size|0.266|0.289|0.227|0.412|0.422|0.371|
||(0.334)|(0.382)|(0.400)|(0.433)|(0.417)|(0.546)|
|Number of women in the household<sup>1</sup>|0.096<br>|0.11<br>|0.088<br>|0.054<br>|0.074<br>|-0.044<br>|
||(0.104)|(0.123)|(0.114)|(0.145)|(0.139)|(0.165)|
|Asset index|0.017|0.061|-0.036|-0.086|-0.063|-0.188|
||(0.132)|(0.146)|(0.181)|(0.204)|(0.202)|(0.195)|
|Total owned land (in acres)|1.018**|1.360**|0.6|0.754|0.943|-0.16|
||(0.428)|(0.528)|(0.512)|(0.543)|(0.572)|(0.388)|
|Average monthly expenditure|473.211|470.616|444.17|267.484|367.439|-297.676|
||(403.795)|(441.530)|(440.550)|(591.398)|(608.246)|(510.030)|
|House quality index|-0.054|-0.078|-0.023|-0.211*|-0.192|-0.314**|
||(0.098)|(0.121)|(0.117)|(0.117)|(0.117)|(0.138)|
|Distance to polling station (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)|
|Low Zaat status|0.026|0.014|0.034|0.063|0.061|0.086|
||(0.059)|(0.070)|(0.067)|(0.101)|(0.099)|(0.069)|
|Received visit from political party staff prior to election|||||||
|(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)|
|Attended political rally before intervention (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|
|P-value F testjoint significance|0.340|0.635|0.971|0.799|0.754|0.466|
|Panel B: Woman Characteristics|||||||
|Age|-0.730|-0.872|-0.674|-1.410**|-1.382**|-1.533**|
||(0.167)<br>|(0.139)<br>|(0.272)<br>|(0.028)<br>|(0.034)<br>|(0.033)<br>|
|Woman has formal schooling (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)|
|Woman is married (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)|
|Number of children under 5 years old|0.088*<br>|0.114**<br>|0.048<br>|0.147***<br>|0.150***<br>|0.137<br>|
||(0.061)|(0.042)|(0.415)|(0.004)|(0.002)|(0.104)|
|Woman has a National Identity Card (NIC or CNIC) (1=Yes|0.027|0.021|0.033|0.042|0.043|0.035|
|<sup>1</sup>|(0.292)<br>|(0.505)<br>|(0.180)<br>|(0.228)<br>|(0.216)<br>|(0.274)<br>|
|Woman voted in last local elections (1=Yes)|0.022|0.002|0.042*|0.036|0.037|0.034|
||(0.333)|(0.942)|(0.095)|(0.232)|(0.223)|(0.307)|
|Access to radio (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)|
|Access to TV (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)|
|Access to cable (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)|
|Mobility Index (0 to 3)|0.032|0.055|0.005|0.012|0.020|-0.034|
||(0.456)|(0.214)|(0.920)|(0.826)|(0.710)|(0.665)|
|Woman allowed to join an NGO (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)|
|Woman is a member of MRDO (1=Yes)<sup>1</sup>|-0.004|0.018|-0.029|0.030|0.023|0.072|
||(0.870)|(0.531)|(0.371)|(0.410)|(0.508)|(0.105)|
|Woman seeks advice from a religious leader or "Pir" (1=Y|-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|
|P-value F test ofjoint significance|0.294|0.057|0.440|0.401|0.305|0.001|

Notes: T refers to the sample of treated households, C control households, CTN control households in treated clusters, TN households in treated clusters (including both treated and control households) and CN households in control clusters (all are control households).<sup>1</sup> indicates that the variable is created using only the sample from the pre-election visit. Variables are defined in Appendix Table A1.
Table 3: Effect on Female Turnout

||Treatment<br>vs control<br>households|Treated<br>clusters vs<br>control<br>clusters|Treated<br>household<br>s only vs<br>control<br>clusters|Control<br>households<br>in treated<br>clusters vs<br>households<br>in control<br>clusters|
|---|---|---|---|---|
||T-C|TN-CN|T-CN|CTN-CN|
||(1)|(2)|(3)|(4)|
|Panel A: Treatment|||||
|Treatment (T)|0.06|0.118|0.120*|0.121*|
||(0.045)|(0.073)|(0.071)|(0.062)|
|R-squared|0.18|0.19|0.19|0.21|
|Panel B: T1vs T2|||||
|Importance of voting (T1)|0.034|0.095|0.094|0.109|
||(0.052)|(0.077)|(0.075)|(0.070)|
|Importance of voting and secret balloting (T2)|0.093*|0.145*|0.152**|0.135*|
||(0.048)|(0.077)|(0.074)|(0.079)|
|R-squared|0.18|0.19|0.2|0.21|
|N. Observations|2,637|2,637|2,304|767|
|Mean dependent variable among CN|0.52|0.52|0.52|0.52|
|_P-value_(T1= T2)|0.223|0.308|0.229|0.752|
|_P-value_(F-test for joint significance of T1and T2)|0.146|0.159|0.106|0.152|

Note: The dependent variable takes the value 1 if a woman reports having voted in the February 2008 elections and had a verifiable ink mark on her thumb. The symbols *, **, *** represent significance at the 10, 5 and 1 percent respectively. All specifications include village fixed effects and the following controls: number of registered female voters, whether woman has a NIC or CNIC, level of schooling, age, zaat status, TV access, number of children between 0-5, total land owned, index of mobility and whether woman seeks advise from "Pir". Standard errors are reported in parentheses below the coefficient and are clustered at the geographic cluster level.
Table 4: Spillover Effects using distance - I

||75m<br>(1)|100m<br>(2)|200m<br>(3)|
|---|---|---|---|
|Panel A: Treatment||||
|Treatment (T)|0.122*|0.153**|0.119*|
||(0.065)|(0.074)|(0.070)|
|Control with T within radius (CT)|0.105*|0.133*|0.072|
||(0.060)|(0.071)|(0.064)|
|Number of households within radius|0.006|0.006*|0.004**|
||(0.004)|(0.003)|(0.002)|
|R-squared|0.19|0.19|0.23|
|_P-Value_(T=CT)|0.612|0.549|0.192|
|Panel B: T1vs T2||||
|Importance of voting (T1)|0.092|0.132*|0.12|
||(0.066)|(0.070)|(0.078)|
|Importance of voting and secret balloting (T2)|0.146**|0.182**|0.167**|
||(0.063)|(0.069)|(0.075)|
|Control with T1 within radius (CT1)|0.045|0.066|-0.004|
||(0.054)|(0.058)|(0.060)|
|Control with T2 within radius (CT2)|0.114*|0.149**|0.151*|
||(0.064)|(0.071)|(0.086)|
|Number of households within radius|0.005|0.005*|0.003*|
||(0.004)|(0.003)|(0.002)|
|R-squared|0.191|0.20|0.20|
|_P-value_(T1= CT1)|0.461|0.350|0.148|
|_P-value_(T2= CT2)|0.418|0.472|0.764|
|_P-value_(T1= T2)|0.245|0.285|0.322|
|_P-value_(CT1= CT2)|0.425|0.392|0.211|
|N. Observations|2,637|2,637|2,637|
|Mean dependent variable among CN|0.58|0.58|0.58|

Note: The dependent variable takes the value 1 if a woman reports having voted in the February 2008 elections and had a verifiable ink mark on her thumb. The symbols *, **, *** represent significance at the 10, 5 and 1 % respectively. All specifications include village fixed effects and the following controls: number of registered female voters, whether woman has a NIC or CNIC, level of schooling, age, zaat status, TV access, number of children between 0-5, total land owned, index of mobility and whether woman seeks advise from "Pir". Standard errors are reported in parentheses below the coefficient and are clustered at the geographic cluster level.
Table 5: Spillover Effects using distance - II

||Mean<br>(1)|Median<br>(2)|Coefficients<br>(3)|
|---|---|---|---|
|Treatment (T)|||0.037<br>[0.031]|
|Number of treated women within 0-200 radius|40.40|35.00|0.007***<br>[0.001]|
|Number of treated women within 200-400 radius|20.47|16.00|0.009***<br>[0.002]|
|Number of treated women within 400-600 radius|11.91|4.00|0.007***<br>[0.002]|
|Number of treated women within 600-800 radius|15.50|6.00|0.005**<br>[0.002]|
|Number of treated women within 800-1000 radius|11.08|1.00|0.005*<br>[0.003]|
|Number of treated women within 1000-1,200 radius|7.88|0.00|0.002<br>[0.003]|
|Number of women within 0-200 radius|56.78|47.00|-0.002**<br>[0.001]|
|Number of women within 200-400 radius|29.84|24.00|-0.004***<br>[0.001]|
|Number of women within 400-600 radius|18.33|7.00|-0.005***<br>[0.001]|
|Number of women within 600-800 radius|21.28|8.00|-0.003*<br>[0.002]|
|Number of women within 800-1000 radius|15.81|4.00|-0.004*<br>[0.002]|
|Number of women within 1000-1,200 radius|11.50|0.00|0.000<br>[0.002]|
|Observations|||2,637|
|R-squared|||0.234|

Note: The dependent variable takes the value 1 if a woman reports having voted in the February 2008 elections and had a verifiable ink mark on her thumb. In column 1, the mean of each variable is reported. Column 2 reports the coefficient along with the standard errors in parentheses below the coefficient, clustered at the gepgraphic cluster level. The symbols *, **, *** represent significance at the 10, 5 and 1 % respectively. All specifications include village fixed effects and the following controls: number of registered female voters, whether woman has a NIC or CNIC, level of schooling, age, zaat status, TV access, number of children between 0-5, total land owned, index of mobility and whether woman seeks advise from "Pir".
Table 6: Spillovers at the Polling Station Level

||(1)<br>W|(2)<br>omen|(3)<br>|(4)<br>Men|
|---|---|---|---|---|
|Panel A: Turnout|||||
|Share of Treated Women|0.864***|0.991***|-0.044|-0.149|
||[0.259]|[0.240]|[0.187]|[0.183]|
|R-squared|0.370|0.601|0.003|0.247|
|Mean of Dependent Variable|0.584|0.584|0.487|0.487|
|Panel B: Share of PPPP|||||
|Share of Treated Women|-0.614**|-0.611*|-0.335|-0.372|
||(0.277)|(0.314)|(0.326)|(0.290)|
|R-squared|0.205|0.237|0.127|0.080|
|Mean of Dependent Variable|0.621|0.623|0.630|0.630|
|Polling Station Controls|No|Yes|No|Yes|
|N. Observations|21|21|21|21|

Note: The dependent variable in Panel A is the share of valid votes cast by women (columns 1-2) and men (columns 3-4) over the total number of registered women/men. In Panel B, the dependent variable is the share of votes obtained by PPPP over the total number of valid votes. 'Share of treated women' is calculated by dividing the total number of women treated, in a polling station, by the number of registered women in the polling station. The symbols *, **, *** represent significance at the 10, 5 and 1 % respectively. Robust standard errors in parentheses.
|Table 7: Effe|Treatment vs<br>control<br>ct on Female PP|Treated<br>clusters vs<br>control<br>PP Vote|Treated<br>households<br>only vs<br>control|Control<br>households<br>in treated<br>clusters vs<br>households<br>in control|
|---|---|---|---|---|
||households<br>T-C|clusters<br>TN-CN|clusters<br>T-CN|clusters<br>CTN-CN|
||(1)|(2)|(3)|(4)|
|Panel A: Treatment|||||
|Treatment (T)|-0.056|-0.157***|-0.146***|-0.218***|
||[0.041]|[0.052]|[0.047]|[0.077]|
|R-squared|0.166|0.175|0.196|0.285|
|Panel B: T1vs T2|||||
|Importance of voting (T1)|-0.023|-0.130*|-0.114*|-0.202**|
||[0.052]|[0.069]|[0.065]|[0.091]|
|Importance of voting and secret balloting (T2)|-0.093|-0.190***|-0.183***|-0.246***|
||[0.057]|[0.057]|[0.055]|[0.090]|
|R-squared|0.171|0.179|0.201|0.286|
|N. Observations|1,133|1,133|974|299|
|Mean dependent variable among CN|0.950|0.950|0.950|0.950|
|_P-value_(T1= T2)|0.328|0.403|0.346|0.652|
|_P-value_(F-test for joint significance of T1and T2)|0.264|0.005|0.004|0.017|

Note: The dependent variable takes the value 1 if a woman reports having voted for PPPP in the February 2008 elections and was verified as having voted. The symbols *, **, *** represent significance at the 10, 5 and 1 percent respectively. All specifications include village fixed effects and the following controls: number of registered female voters, whether woman has a NIC or CNIC, level of schooling, age, zaat status, TV access, number of children between 0-5, total land owned, index of mobility and whether woman seeks advise from "Pir". Standard errors are reported in parentheses below the coefficient and are clustered at the geographic cluster level.
Table 8: Effect on Candidate Choice Using Cross Reports from Family Members

||Treated<br>clusters vs<br>control<br>clusters<br>TN-CN<br>(1)|Treated<br>households<br>only vs<br>control<br>clusters<br>T-CN<br>(2)|Control<br>households<br>in treated<br>clusters vs<br>control<br>clusters<br>CTN-CN<br>(3)|
|---|---|---|---|
|Panel A: Treatment||||
|Treatment (T)|-0.007|-0.015|0.024|
||(0.023)|(0.025)|(0.025)|
|Man reporting about woman|-0.012|-0.010|-0.021|
||(0.019)|(0.019)|(0.020)|
|Man reporting x T|-0.085***|-0.082***|-0.104*|
||(0.027)|(0.028)|(0.054)|
|R-Squared|0.065|0.069|0.125|
|Panel B: T1vs T2||||
|Importance of voting (T1)|-0.016|-0.026|0.012|
||(0.026)|(0.028)|(0.025)|
|Importance of voting and secret balloting (T2)|0.002|-0.003|0.024|
||(0.027)|(0.030)|(0.029)|
|Man reporting about woman|-0.012|-0.010|-0.021|
||(0.019)|(0.019)|(0.020)|
|Man reporting x T1|-0.064*|-0.072*|-0.025|
||(0.037)|(0.039)|(0.040)|
|Man reporting x T2|-0.107***|-0.093**|-0.189**|
||(0.032)|(0.035)|(0.084)|
|R-squared|0.064|0.070|0.126|
|N. Observations|3,713|3,200|914|
|Mean dependent variable among CN|0.983|0.983|0.983|
|_P-value_(T1=T2)|0.475|0.431|0.688|
|_P-value_(Male Report x T1=Male Report x T2)|0.313|0.659|0.067|

Note: The dependent variable takes the value 1 if a woman's self-report about candidate choice matches the report of the reportee, either another woman in the household or the male head. Each observation is therefore a pair with several observations for each woman. If a reporter believes that a woman did not vote or does not know whom she voted for, the dependent variable is coded as missing. All specifications include village fixed effects and the following controls: number of registered female voters, whether reportee has a NIC or CNIC, level of schooling, age, zaat status, TV access, number of children between 0-5, total land owned, index of mobility and whether woman seeks advise from a "Pir". Standard errors are reported in parentheses below the coefficient and are clustered at the geographic cluster level. The symbols *, **, *** represent significance at the 10, 5 and 1 % respectively.
Table 9: Effect on Knowledge and Perceptions

||N. Obs|Index of<br>knowledge<br>of current<br>events|Index of<br>opinion on<br>democracy|Woman<br>checked<br>voter list<br>after<br>intervention|Woman<br>believes<br>elections<br>were free and<br>fair|Woman<br>witnessed or<br>heard about<br>violence in<br>village|
|---|---|---|---|---|---|---|
||(1)|(2)|(3)|(4)|(5)|(6)|
|Treated clusters vs control clusters (TN-CN)|2637|0.005|0.066|0.051*|0.070**|-0.104**|
|||(0.072)|[0.041]|(0.030)|(0.034)|(0.044)|
|Treated households only vs control clusters (T-CN)|2304|0.012|0.069|0.053*|0.075**|-0.101**|
|||(0.070)|[0.042]|(0.031)|(0.033)|(0.042)|
|Control households in treated clusters vs|767|-0.025|0.046|0.048|0.060|-0.122**|
|households in control clusters (CTN-CN)||(0.094)|[0.052]|(0.035)|(0.037)|(0.049)|
|Mean dependent variable among CN||0.00|-0.03|0.61|0.88|0.27|

Note: The symbols *, **, *** represent significance at the 10, 5 and 1 % respectively. All specifications include village fixed effects and the following controls: number of registered female voters, whether woman has a NIC or CNIC, level of schooling, age, zaat status, TV access, number of children between 0-5, total land owned, index of mobility and whether woman seeks advise from "Pir". Standard errors are reported in parentheses below the coefficient and are clustered at the geographic cluster level. Variables are defined in Appendix Table A1.
Table A1. Definition of Variables

|Variable|Definition|
|---|---|
|**Polling Station Characteristics**||
|Share Valid Votes|Share of valid votes cast by women (columns 1-2) and men (3-4)|
|Share PPP|Share of votes obtained by PPPP over the total number of valid votes|
|Share of treated women|calculated by dividing the total number of women treated, in a polling station, by the number of registered women in the polling station.|
|St. Dev of asset index|Standard Deviation of household asset Index|
|St. Dev of distance to polling station|Standard deviation of distance to polling station|
|Pct. of Women with Access to Cable TV|Percentage of Women with Access to Cable TV|
|**Household Characteristics**||
|Household size|Total number of individuals in the household including children|
||The first component of a PCAincluding the number of refrigerators, freezers, fans, geysers, washing machines/dryers, cooking stoves, TVs, VCRs, VCPs/ CD|
|Asset Index|players, Radios/ cassette players, sewing/knitting machines, dish antennas, cable services, bicycles, motorcycles, cows, buffalos and goats, as well as a<br>dummy variable that takes value 1 if household owned any major agricultural assets/ machinery.|
|Total owned land (in acres)|Total acres of owned land by the household|
|Averae monthl exenditure (in|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|
|g y p<br>thousands)|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<br>than 15,000 but less than 25,000, greater than 25,000 but less than 35,000.|
||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|
|House quality index|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<br>and the main source of drinking water for the household is either piped water or hand pump.|
|Distance to polling station (Km.)|Total distance in Km. from household to polling station.|
|Low Zaat (Caste) Status|Household belongs to service or menial zaat groups|
|**Woman Characteristics**||
|Woman has formal schooling (1=Yes)|Dummy variable equal to 1 if woman has any formal schooling.|
|Woman is married (1=Yes)|Dummy variable equal to 1 if woman is married.|
|Number of children under age 5|Number of children under 5 years old over total number of children that the woman has.|
|Woman would be allowed to join a NGO<br>(1=Yes)|Dummy variable equal to 1 if woman would be allowed to get involved in an NGO if one were to start working in their village.|
|Has a NIC (1=Yes)|Dummy variable equal to 1 if the woman has a national identity card|
|Access to radio (1=Yes)|Dummy variable equal to 1 if woman has access to a radio.|
|Access to TV (1=Yes)|Dummy variable equal to 1 if woman has access to TV.|
|Access to cable (1=Yes)|Dummy variable equal to 1 if woman has access to cable.|
|Hours of Radio in an average week|The product of number of hours of radio listened in an average day times number of days respondent listens to the radio in an average week.|
|Gets World new from BBC's Urdu Service|Dummy variable equal to 1 if respondent reported turning to BBC radio first for getting world news|
|Number of hrs of TV watched in avg week|The product of number of hours of TV watched in an average day times number of days respondent watches TV in an average week|
|<br>|<br>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|
|Mobility Index|,<br>to all three; 2=accompanied by adult male and 3= Accompanied by adult female, children or alone. The index is the sum of responses divided by 3|
|MRDO membership (1=Yes)|Dummy variable equal to 1 if woman is a member of a community organization in her village.|
|Index of community action taken|Index constructed using prinicipal components analysis of 3 questions on methods tried to resolve different situations for both men and women(election<br>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 of contact with formal authority|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<br>councilor (Nazim, Naib Nazim) and contacted a political party official. The total is divided by 2.|
|Index of contact with informal authority|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<br>(Pir, Murshid) and contacted a traditional ruler (Wadera, Maalik, Numberdar). The total is divided by 2.|
Table A1. Definition of Variables (cont.)

|Variable|Definition|
|---|---|
|**_Knowledge of current events and the politic_**|**_al process_**|
|Aware of imposition of Emergency Rule<br>(1=Yes)|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<br>house arrest of various lawyers.|
|Index of knowledge of current events|Average score of the following knowledge questions: "Aware of imposition of emergency/house arrest of lawyers and removal of Chief Justice" and "Knows<br>name of newly elected Prime Minister".|
|Share of political party signs correctly<br>identified|Proportion of signs (outof 7) that respondent were able to correctly match to a political party contesting for a National Assembly seat.|
|Share of political party names correctly<br>identified|Proportion of party's names contesting for National Assembly that the respondent was able to recall perfectly out of 2.|
|Recalls winning candidate (1=Yes)|Dummy variable equal to 1 if woman perfectly recalled the name of the candidate that won the National Assembly seat in her constituency|
|Recalls names of main candidates (1=Yes)|Dummy variable equal to 1 if woman perfectly recalled the names of the candidates from the two main parties that contested a National Assembly seat|
|Knows the gender of main candidates<br>(1=Yes)|Dummy variable equal to 1 if woman perfectly identified the gender of the candidates from the two main parties that contested a National Assembly seat|
|**_Voting behavior and perceptions_**||
|Checked voter list after February 5th<br>(1=Yes)|Dummy variable equal to 1 if after February 5th woman or a family member checked to see if she was on the voter list.|
|Voted in last elections (local) (1=Yes)|Dummy variable equal to 1 if woman voted in the last local body elections.|
|Voted in Feb 08 (1=Yes)|Dummy variable equal to 1 if respondent voted in this national elections.|
|Witnessed or heard of any type of<br>violence in/near village (1=Yes)|Dummy variable equal to 1 if woman personally witnessed or heard of any type of violence in/near her village.|
|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<br>with minor problems" instead of "Free and fair but with minor problems" and "Not free and fair".|
|Index of opinion on democracy|Disagreement with the following statement: "Only educated should vote" and average disapproval of the following forms of government: "Only one party is<br>allowed to stand for election and hold office. ", "The army comes in to govern the country", "There are no elections, no MPA or MNA and the president|
|**_Recall of Intervention_**||
|Visit before elections (1=Yes)|Dummy variable equal to 1 if woman confirmed in the follow-up survey that she was visited before the elections to tell her about the importance of the<br>elections and voting.|
|Present in visit before elections (1=Yes)|Dummy variable equal to 1 if woman confirmed in the follow-up survey that she was present in the visit before the elections to tell her about the importance<br>of the elections and voting.|
|Attend presentation in a neighbor's|<br>Dummy variable equal to 1 if woman confirmed in the follow-up survey that she was present in the visit that took place in a neighbor's house before the|
|house (1=Yes)|elections to tell them about the importance of the elections and voting.|
|Neighbors joined during visit (1=Yes)|Dummy variable equal to 1 if woman confirmed in the follow-up survey that some neighbors were present in the visit that took place at her house before the<br>elections to tell them about the importance of the elections and voting.|
|Issues raised: importance of voting<br>(1=Yes)|Dummy variable equal to 1 if woman confirmed in the follow-up survey that the issue raised during the visit before the elections was about the importance<br>of voting.|
|Issues raised: importance of secret voting<br>(1=Yes)|<br>Dummy variable equal to 1 if woman confirmed in the follow-up survey that the issue raised during the visit before the elections was about the importance<br>of voting secrecy.|
|Issues raised: importance of voting and<br>secrecy (1=Yes)|Dummy variable equal to 1 if woman confirmed in the follow-up survey that the issues raised during the visit before the elections were the importance of<br>voting and importance of voting secrecy.|
|Talked about visit (1=Yes)|Dummy variable equal to 1 if woman confirmed in the follow-up survey that she talked about the visit and the issues raised during the visit with others in her<br>neighborhood.|
|Neighbor talked about meeting to|Dummy variable equal to 1 if woman confirmed in the follow-up survey that some women from her neighborhood talk to her about the meeting which she|
|woman (1=Yes)|had attended in the days preceding the election.|
Table A2. Gender Differences

|||Me|ans|P-value<br>|
|---|---|---|---|---|
||(1)<br>N. Obs|Female<br>(2)|Male<br>(3)|(4)<br>of t-test<br>of (2)-(3)|
|Panel A: Access to Media|||||
|Access to Radio (1=Yes)|1,923|0.47|0.42|0.061|
|Number of hours of radio listened to in an average week|852|9.7|9.63|0.867|
|Access to TV (1=Yes)|1,923|0.67|0.629|0.103|
|Number of hours of TV watched in an average week|1,222|15.3|11.0|0.000|
|Access to cable TV (1=Yes)|1,923|0.29|0.23|0.008|
|Listens to BBC's urdu service for world news(1=Yes)|852|0.10|0.48|0.000|
|Panel B: Knowledge of Political Parties and Elections|||||
|Share of political party signs correctly identified|1,923|0.28|0.42|0.000|
|Share of political party names correctly identified|1,923|0.86|0.96|0.000|
|Knows the gender of main candidates (1=Yes)|1,923|0.95|0.98|0.483|
|Recalls names of main candidates (1=Yes)|1,923|0.82|0.86|0.488|
|Recalls winning candidate (1=Yes)|1,923|0.90|0.95|0.219|
|Aware of EmergencyRule(1=Yes)|1,923|0.10|0.51|0.000|
|Panel C: Participation in Public Life|||||
|Attends community meetings (1=Yes)|1,923|0.18|0.52|0.000|
|Attends demonstrations (1=Yes)|1,923|0.12|0.23|0.000|
|Attended political rally before intervention (1=Yes)|1,923|0.05|0.24|0.000|
|Takes action|||||
|If name missing in voter list (1=Yes)|1,923|0.76|0.92|0.000|
|If police mistakenly arrest family member (1=Yes)|1,923|0.93|0.98|0.000|
|If family land is seized (1=Yes)|1,923|0.92|0.98|0.000|
|Index of community action taken|1,923|-0.29|0.69|0.000|
|Contacts local councilor (1=Yes)|1,923|0.25|0.37|0.000|
|Contacts a local political party official (1=Yes)|1,923<br>,|0.22|0.38|0.000|
|Index of formal authority contact|1,923|-0.10|0.34|0.000|
|Contacts a religious leader (1=Yes)|1,923|0.66|0.49|0.000|
|Contacts a traditional ruler (1=Yes)|1,923|0.45|0.32|0.000|
|Index of informal authoritycontact<br>|1,921<br>|0.12<br>|-0.30<br>|0.000<br>|

~~Note: Data come from follow-up survey. Male refers to head of household while female to their~~ spouse. P-values were calculated from a regressions of each variable on a gender dummy. The regression included village fixed effects and standard errors were clustered at the geographical cluster level.
Table A3. Attrition

||Women|Level|Househol|d Level|
|---|---|---|---|---|
|Panel A: Treatment|(1)|(2)|(3)|(4)|
|Treatment (T)|-0.004|-0.003|0.01|0.011|
||(0.010)|(0.011)|(0.009)|(0.010)|
|Baseline Contols?|N|Y|N|Y|
|R-squared|0.02|0.02|0.00|0.00|
|Panel B: T1vs T2|||||
|Importance of voting (T1)|-0.022|-0.022|-0.004|-0.004|
||(0.012)|(0.012)|(0.011)|(0.011)|
|Importance of voting and secret balloting (T2)|0.020|0.021|0.029*|0.030**|
||(0.013)|(0.017)|(0.014)|(0.015)|
|Baseline Contols?|N|Y|N|Y|
|R-squared|0.03|0.03|0.01|0.01|
|Mean dependent variable|0.035|0.035|0.026|0.026|
|Observations|2,734|2,734|1,019|1,019|

Note: Regressions (1) and (2) are at the women level and (3) to (4) are at the household level. In the latter the controls take the average value of the women within a household. The dependant variable takes the value 1 if woman attrited. All regressions include village fixed effects and the following control variables collected during pre-election visit are included when noted: Woman has NIC or CNIC, voted in last elections, woman is a member of MRDO and the number of females in the household. Standard errors are reported in parenthesis below the coefficients and are clustered at the geographical cluster level. The symbols *, **, *** represent significance at the 10, 5 and 1 % respectively.
|Table A4. Information about interv|ention a|nd abou|tpoliti|cal disc|ussions||C in|C in|C in<br>control|
|---|---|---|---|---|---|---|---|---|---|
||N. Obs|All|T|T1|T2|C in T|<br>T1|<br>T2|<br>clusters|
||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|(9)|
|Panel A: Information about visit||||||||||
|Received visit before elections (1=Yes)|2,637|0.71|1.00|1.00|1.00|0.00|0.00|0.00|0.00|
|Neighbors joined during visit (1=Yes)|1,867|0.11|0.11|0.08|0.15|--|--|--|--|
|Issues raised during visit||||||||||
|Importance of voting|1,867|0.64|0.64|0.98|0.19|--|--|--|--|
|Importance of voting in accordance to own preferences|1,867|0.06|0.06|0.02|0.12|--|--|--|--|
|Both|1,867|0.30|0.30|0.01|0.69|--|--|--|--|
|Discussed visit with neighbors(1=Yes)|1,867|0.41|0.41|0.35|0.50|--|--|--|--|
|Panel B: Information about political discussions||||||||||
|Discuss political issues with women in neighborhood (1=Yes)|2,637|0.44|0.55|0.50|0.62|0.40|0.30|0.51|0.18|
|Issues raised during conversations||||||||||
|Party/Candidate Positions|847|0.61|0.62|0.61|0.63|0.59|0.58|0.61|0.59|
|Importance of voting|847|0.86|0.85|0.85|0.86|0.86|0.89|0.83|0.88|
|Importance of voting in accordance to own preferences<br>Notes: Data come from follow-up survey. Column (1) refers to th<br>data for treated women. Columns (6)-(8) report data for control<br>women in control clusters.|847<br>e numbe<br>women i|0.52<br>r of ob<br>n treat|0.53<br>servati<br>ed clus|0.53<br>ons for<br>ters. Co|0.53<br>column<br>lumn (9|0.47<br>(2). Co<br>) repor|0.49<br>lumns<br>ts data|0.45<br>(3) -(5<br>for co|0.51<br>) report<br>ntrol|
Table A5: Impact on Women's Participation and Candidate Choice

||All|_t_<br>Women|_P-_<br>_value_<br>_of t-_<br>_est (1)-_<br>|Not vote|<br>d in the|_P-value_<br>_of t-test_<br>past|Vote|d in the|_P-value_<br>_of t-test_<br>past|
|---|---|---|---|---|---|---|---|---|---|
||T|CN|_(2)_|T|CN|_(4)-(5)_|T|CN|_(7)-(8)_|
||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|(9)|
|Percentage of women who||||||||||
|Voted for the same party as male head|44.6|41.7|0.500|13.5|11.6|0.326|57.25|56.94|0.950|
|Voted for different party from head|10.1|2.8|0.010|2.2|1.4|0.647|13.15|3.47|0.000|
|Voted but male head did not|6.1|3.7|0.220|1.7|2.7|0.274|7.89|4.17|0.090|
|Did not vote|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||

Note: P-values are from regressions with village fixed effects, woman characteristics as controls and robust standard errors clustered at the geographic cluster level. The symbols *, **, *** represent significance at the 10, 5 and 1 % respectively.