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Entry, Exit and Candidate Selection: Evidence from India Abhijit V Banerjee Esther Duflo Clement Imbert Rohini Pande October 28, 2016 Keywords: JEL: Abstract What motivates candidates to run in low income democracies? We examine the electoral impact of a voter awareness campaign which emphasized the responsibilities of local leaders in implementing a nation-wide public employment program. The intervention led to exit by the worse performing incumbents, substitution by incumbent family members and entry by challengers from traditionally disadvantaged groups. We contrast these effects with those of previous reservation for women, which weakens the incumbent who faces greater social pressure to not re-run. Previous reservation had similar effects on incumbency, accountability, and challenger entry, but did not change the composition of the candidate pool. This suggests that the wider political representation due to the campaign is not a mechanical effect from weakening the incumbent but reflects the motivation of candidates from disadvantaged groups to be in charge of the program. We find no evidence of a cumulative effect of the campaign with previous reservation. We would like to thank Aparna Krishnan, Vipin Awatramani, Dinesh Bhatt, Nikhil Dev, Avnish Gungardurdoss and Harsh Gupta for field work and Jeff McManus for exceptional research assistance. Thanks to Sharun Mukhand and Patrick Francois for helpful comments. Abhijit Banerjee and Esther Duflo: MIT; Clement Imbert: Warwick University; Rohini Pande: Harvard University. Protocol 091003477). The project was approved by the Institutional Review Boards at Harvard, and MIT (COUHES 1

1 Introduction There is broad agreement that the effectiveness of democratic governance rests, to a large extent, on whether high quality citizens enter politics (Myerson (2011)) and on whether citizens reward quality and performance at election time (Besley, 2007). There is also a concern that entrenchment of the economic elite in politics may prevent this process in many low-income democracies (Acemoglu and Robinson, 2008). A growing body of evidence demonstrates the importance of entry costs in affecting candidate entry (Chattopadhyay and Duflo (2004)) and of voter information (awareness) for candidate selection (Ferraz and Finan, 2008; Banerjee et al., 2011). However, our evidence base on how these factors influence incumbent decisions to re-run and resulting strategic interactions across candidates is much more limited. We also know less about the implications for the quality of governance. In this paper we examine these issues in the context of elections for local village council head in the Indian state of Rajasthan in 2010. In our sample of 382 village councils, two exogenous factors influenced citizens entry decision and subsequent voter behavior. First, a random sample of councils had been reserved in the previous electoral cycle for women. To the extent that these women had been first time entrants into politics and faced greater family pressure to not rerun, challengers could anticipate a lower probability that the incumbent would run for election. Second, voters in a random sample of councils were exposed to a pre-election voter awareness campaign (now on, PEVAC) in which they were informed about the responsibilities of the council head in implementing a large public works program and average incumbent performance (across a large set of village councils, which included theirs) in implementing this program. In a subsample of PEVAC councils, the campaign also emphasized the fact that the performance of female incumbents was similar (if not better) than male incumbents. The PEVAC treatment occurred in the month prior to election (when candidates still made entry decisions). It, thus, both provided potential challengers with more information on the returns to political office and depending on incumbent performance may have either strengthened or weakened the incumbency advantage and, therefore, the incumbent decision on whether to run. What are the likely impacts of these two exogenous shocks? The seminal papers on citizen entry into politics, which allow for strategic choices, are the citizen candidate models of political 2

competition (Besley and Coate, 1997; Osborne and Slivinski, 1996). These papers identify policy preferences of other candidates and probability of electoral success (running is assumed to be costly) as determinants of a candidate s decision to run. A natural enrichment of this model is to assume that candidates also enjoy private rents to office. Caselli and Morelli (2004) show that if several candidates are running, but voters have limited ability to distinguish between good and bad candidates, then the winning probabilities are small and highly skilled citizens may prefer to not enter politics. That said, if candidate entry aids learning about candidate type then increased candidate entry may improve outcomes in a dynamic setting. 1 On the other hand, more candidate entry also increases the challenge for voter coordination. To summarize, these models predict that reductions in entry costs (in our case, due to reduced incumbency advantage) should encourage candidate entry. Who enters is less clear, and will depend on the heterogeneity of preferences in the population, on the private returns to political office and on the quality distribution among potential candidates. The implications for the quality of elected officials, in turn, depends on voter information about candidate quality and their ability to coordinate their voting decisions. From our experiments, the first finding is that both the end of mandated representation for women and greater citizen awareness about the returns to political office and average quality of incumbents (from the PEVAC) reduced the likelihood that the incumbent chose to run for re-election. Specifically, (female) incumbents in previously reserved councils are less likely to re-run than the (typically male) incumbents in previously un-reserved councils (14.8% versus 46.2%). Second, the PEVAC reduced the probability that a (typically male) incumbent (in a previously unreserved seat) would run again by 27 percentage points (more than a half), and reduced the vote share going to a typically male incumbent by about the same proportion. 2 1 For example, we could think of a dynamic extension of the Caselli and Morelli framework, where candidates need to enter for voters to learn their types and the presence of a very good incumbent makes it so unlikely that any new entrant would win that essentially no one enters and no one learns their type, making the eventual transition after the incumbent retires less efficient. Or there may be voter inertia: Myerson (1993) argues that good candidates may not join the race because there is a small group of established but not necessarily good candidates who have traditionally attracted all the votes, and no voter will (rationally) want to be the only one switching her vote to a new candidate. In other words there may be a coordination failure, with too little entry. Caselli and Morelli (2004) rule this out by assuming that voters vote sincerely rather than strategically. 2 Interestingly, in contrast to the voter campaign or the reservation policy, the version of the campaign that 3

The latter finding is consistent with the fact that the average incumbent performance in the public works program was relatively poor. If we use a broader measure of incumbency whether the incumbent or a member of her family stood for election then the impacts of reservation and PEVAC on the probability of running are much smaller, and become insignificant. In the case of reservation this is consistent with the idea that the spouse of the female incumbent is the long-run political actor in the household, and replaces the female incumbent when reservation ends. The fact that PEVAC leads to intra-family substitution suggests a strategic response; our finding resonates with Querubin (2011) finding on term limits in the Philippines. A key feature of the PEVAC campaign was the focus on performance in the public employment program. We construct an index of incumbent performance using publicly available statistics on program implementation (number of man days generated), combined with measures from a household survey, and a survey of village assets built under the employment program program, both of which we conducted for the purpose of this study. The anti-incumbent impact of both PEVAC and becoming unreserved are much more muted for better performing incumbents. Thus, it appears that the anti-incumbent impact of the campaign was strongest for the worst performing incumbents. Using a broader definition of incumbency which includes the family members only strengthens this result. Alongside, we observe candidate entry. Both reservation and the PEVAC increased the number of candidates by one (on a basis of about seven). The number of literate candidates went up by one as well, and the number of candidates with political experience in lower offices (councilor position) increased. In previously reserved councils, an important influence appears to be more citizen acceptance of female candidates so while the female incumbent was less likely to run, we also observe an increase in the number of female challengers. This finding is similar to Beaman et al. (2009). Most of the increase in the number of candidates due to the PEVAC treatment is attributable to candidates belonging to traditionally less advantaged lower caste groups (scheduled caste, scheduled tribes, or other backward castes). As before, the gender-focused campaign had no impact. Finally, reservation and PEVAC do not seem to focused on getting women to run (and voters to vote for them) had no impact on candidate entry or incumbent behavior. We discuss reasons why this might have happened in section 4.4. 4

have had a cumulative impact on any of these dimensions. The only additive effect of these interventions is on encouraging more landless candidates to enter the race. In terms of who won, we see that PEVAC increased the likelihood that a non-general caste candidate won. It also increased the likelihood that the winning candidate was literate and had previous experience as a councilor. Turning to the impact of PEVAC on quality of newly elected council head, we have some suggestive evidence that performance as measured by the number of jobs generated under the employment guarantee scheme was worse as reported in the official statistics, 3 while the number of public goods built was unchanged (as reported in a survey we conducted). A key outcome, which we are currently investigating, is whether the distribution of where public goods were placed was altered. These effects are absent in the case of reservation, potentially because reservation did not change either the caste or the political experience of the new council head. To the extent that the differential performance of new leaders in PEVAC councils reflects either lower (or different) political experience or changing preferences neither effects are present in previously reserved councils. Overall, these results demonstrate both the importance of strategic behavior in politicians decisions to run, and the role of incumbency advantage in influencing the costs of entry faced by potential challengers. On the one hand if we were to measure the success of reservation and PEVAC by representation, then both interventions led to entry and greater electoral success for historically disadvantaged groups women and lower castes. On the other hand, if we measure the campaign success by short-run incumbent performance then it does appear that entry by new entrants (with likely less political experience) can lead to worse performance in the short-run. There is a rich theoretical (Barro, 1973; Ferejohn, 1986; Persson et al., 1997) and more recently empirical (Ferraz and Finan, 2008; Banerjee et al., 2011) litterature on the effect of political information on governance outcomes. One key insight of this literature is that information about the incumbent s performance while in office will be used at the time of the elections by voters to sanction bad politicians. However, even if in the long run more information should help select better politicians, the short term implications of exposing the incumbent on the quality 3 This measure may exaggerate the advantage of incumbents who knows the system. 5

of the challengers who enter the race and on the performance of the elected candidate are less clear. Related empirical work includes Diermeier et al. (2005) and Keane and Merlo (2010) who estimate structural models of entry decisions of US legislators where the emphasis, as in Caselli and Morelli (2004) is on the role of the outside option. They find evidence that highly skilled people are more likely to exit politics, especially when congressional salaries are low. In Ferraz and Finan (2009), higher wages both increase the number of candidates and improves the quality of legislators. However, these papers assume that the likelihood of winning is a candidate characteristic, i.e. they do not allow for strategic elements in the entry/exit decision. Section 2 describes the context of our study, the electoral interventions and identifies their likely impacts. Section 3.1 describes the data and empirical strategy. Section 4 reports our experimental findings and Section 5 concludes. 2 Background 2.1 Electoral context Our focus is on village council or Gram Panchayat (hereafter GP) elections. This is the lowest tier of elected representation in India, which is responsible for the provision of village infrastructure (public buildings, water, roads, etc.) and for identifying welfare recipients within the villages. Since 2006, the GP is also responsible for the administration of the federal government s flagship anti-poverty program, the Mahatma Gandhi Rural Employment Guarantee Act (MGN- REGA). The act entitles every rural household to 100 days of work per year at the state-statutory minimum wage. The GP is in charge of registering potential beneficiaries, planning and executing public works 4, providing employment upon request and insuring timely payment of wages to the workers. In Rajasthan, the setting for our study, the typical Gram Panchayat (GP) has an electorate of roughly 3,000 spread across multiple villages. The GP is divided into electoral wards, and a 4 The village general assembly, or Gram Sabha decides every year on a shelf of projects. The head of the Gram Panchayat selects and executes works depending on the demand for work. 6

ward councilor is directly elected from each ward by plurality rule every five years. In addition, in Rajasthan, the Sarpanch (head councilor) is also elected by direct vote. GP council decision-making is by majority voting. However, while the Sarpanch does not have formal veto power, he or she is the only full-time member of the council and exercises significant control over the final council decisions (Besley et al., 2012). Our experiment therefore, focused on the Sarpanch election. Our evaluation occurred in the context of the 2010 Sarpanch elections which were held between 22nd January and 4th February 2010. It focuses on 382 GP, which constituted all Sarpanch seats not reserved for women in three districts of Eastern Rajasthan: Bharatpur, Dholpur and Karauli. Below, we describe the two cross-cutting interventions which we exploit in our analysis. 2.2 Reservation The introduction of elected GP in 1993 was accompanied by electoral quotas for disadvantaged minorities and for women, a policy which has led to a dramatic rise in local female leadership across Indian villages. Each Indian state is required to reserve at least 1/3 of elected Sarpanch positions for women, but each state separately decides the rules for implementing political reservation. In Rajasthan, GP to be reserved for women are randomly selected at each election. At the time of our evaluation, two electoral cycles had been completed with reservation: in 2000 and 2005. For these two elections, reserved GP were selected by rotation; in principle the villages that had been reserved in 2000 were excluded from randomization in 2005, although there is a couple of exceptions in our data. For 2010 elections, 50% of the GP were randomly selected to be reserved for women regardless of their previous reservation status; our evaluation focuses on the remaining 50%. By law each Indian state is also required to reserve some GP for disadvantaged minorities (low caste and tribals). In each district of Rajasthan, the percentage of GP reserved for each minority was fixed to reflect their share in the total population, and GP with the highest population share of each group were selected for reservation. In 2005 and 2010, reservation was rotated in a non transparent way. The reservation for caste and the reservation for women were done 7

independently for each election, so that the probability of being reserved for women in 2010 or having been reserved in 2000 and 2005 should be the same for all GP, regardless of their caste reservation status in 2010 or in previous elections. In our sample of GP not reserved for women, 16% were reserved for Other Backward Castes (OBC) in 2010, 23% for Scheduled Castes (SC) and 11% for Scheduled Tribes (ST) so that the incumbent could only run in 64% of the GP In our analysis, we take advantage of the random assignment of GP to be reserved for women to identify the impact of past reservation for women. However, because of the endogenous selection of GP reserved for minorities, we control for caste reservation status in 2010, but we cannot identify the impact of caste reservation per se. 2.3 Voter Awareness campaigns The second intervention exploited in our analysis is an awareness campaign, which used calendars, door-to-door canvassing and street theater to convey information about Sarpanch responsibility in providing public goods and employment to the villages. The main objectives were to prompt voters and potential candidates to participate to the elections and to focus on performance, instead of caste or gender. There were two versions of the campaign, which used two different sets of calendars and two different scripts for the plays, which we will refer to as the general campaign and the gender campaign. The general campaign emphasized that beyond caste or gender only performance mattered to choose the right candidate. The street play illustrated the importance of electing a wellperforming leader by comparing one village where public infrastructure (roads or hand pump for drinking water) was well maintained with another village where public infrastructure was poor. District average statistics on MGNREGA implementation were printed on the calendar and read out during the play to highlight the fact that the Sarpanch played an important role in providing employment to the community. 5 The campaign did not disclose information on the level of MGNREGA implementation in each GP along with district averages. The reason was to 5 The statistics used were expenditures per GP, share of participant households and number of working days per participant household, which we downloaded in December 2009 for each district from the official website http:\\nrega.nic.in. They were hence publicly available information, in contrast with the data from the household and asset surveys which we use for the purpose of the analysis. Two samples of the calendar are shown in Appendix (figures A.1 and A.2). 8

avoid being unfair vis-a-vis the incumbent, because for example lower than average MGNREGA expenditures could reflect low demand for work in the GP rather than low supply of public employment. Honest and effective citizens were encouraged to run as candidates and voters were encouraged to take such candidates seriously. The gender campaign incorporated the elements of the general treatment. In addition, it provided the message that both genders could run in unreserved councils, and that women Sarpanch (from reserved GP) typically performed as well as men. To illustrate the first message, the play depicted a male candidate who attempted to forbid to a woman to run against him, but was forced by village elder to admit that she had the right to run. To illustrate the second message, statistics on MGNREGA implementation in GP reserved for women in 2005 and in unreserved GP were printed on the calendars and compared during the play. The modus operandi was similar to other pre-election information campaigns done by NGOs or by the government in Rajasthan. Street plays are frequently used to raise awareness about particular issues (e.g. HIV) in rural areas, where the reach of newspapers, radio and television is still very limited. 6 It was implemented by Prayatn, a NGO based in Jaipur (Rajasthan), which hired teams of actors, dancers and singers for the purpose of the campaign. Prayatn had been hired by the government to raise awareness about the National Rural Employment Guarantee Scheme when it was launched in Karauli in 2006. 7 The intervention took place in a randomly selected set of 119 GP (out of our full sample of 382 GP). The campaign schedule was organized in order to minimize the time to the elections; in practice the teams visited the GP between one and 20 days (10 days on average) before the elections. Close as it was to the election, the campaign still happened before candidates registered: candidate registration in every GP occurred the day before the elections. In the treatment GP, the campaign teams visited all villages with more than 300 inhabitants, 439 villages in total. A team would typically go to the main village in the morning to distribute calendars and advertize the evening show. It would then travel to a second, smaller village, where the distribution of calendars and the show would happen in a 2 hours sequence around noon. 6 The campaign drew from a vast repertoire of songs written in Rajasthani dialects for awareness campaigns, including songs about elections for get-out-the vote campaigns, and songs about the right to employment for the launch of the MGNREGA. 7 Website: http://prayatn.org/ 9

After covering a third, smaller village in the afternoon, the team would go back to the main village and make an evening show. Villages with more than 1000 inhabitants had two shows, set in different neighborhoods. In total, a team of 60 members performed in 439 villages (all villages of more than 300 inhabitants were covered, a Panchayat generally has 4 large villages). Monitors were sent with each team to check if the protocol was followed and to record the number of calendars distributed and the number of male and female adults who attended the shows. The campaign was well implemented and popular with villagers. In total, 472 shows took place (the bigger villages had 2 shows), on average 234 people (32% of the adult population) attended the show in each village, and 130,000 calendars were distributed. 8 Among the adults who attended the show, the proportion of women was 41% overall, with some variation depending on the time of the day when the show was held (only 35% of women after 6pm). Finally, there was substantial variation of attendance rates across GP, with less than 12% of the adults who attended the show in the bottom 10% of GP and more than 55% of adults who attended in the top 10% of the GP. In order to better understand the determinants of attendance to the shows, we regress the log of total attendance and the log of female attendance on a vector of Panchayat characteristics. The results are presented in Table A.3. Not surprisingly, total attendance to the shows was higher in GP where the campaign team performed more shows. Apart from the number of shows, the only significant predictor of total attendance is the literacy rate. Interestingly, we find that female attendance to the shows is higher in GP that were previously reserved for women (in 2000 or 2005). This finding is consistent with the idea that women reservation increases political participation of women. Finally, we find some evidence that female attendance is higher in GP reserved for OBC, and lower for GP reserved for ST, even controlling for the fact that these GP have a larger ST population. This suggests that voters are less interested in the elections when the Sarpanch seat is reserved for a minority (ST represent 26% of the population of GP reserved for ST). 8 To obtain these figures we completed monitors reports with census 2001 and 2011 information for each village. Using 2001 census figures, we assumed that 50% of the population was adult, and that each household had 6 members. Finally, we applied to the 2001 village population totals a 19% of decadal population growth rate, which matches 2011 census results in the sample districts. 10

3 Data 3.1 Data sources This study relies on five different data sources: two administrative sources and three surveys. The first administrative source is the State Election Commission (SEC) from which we collected 2010 electoral results for all 382 GP. In each GP, the SEC records the names, caste and votes received by each candidate, in addition to the name of the winner. Based on this list, we construct measures of the number of candidates in total, by gender, and by caste, as well as their share of votes and their probability of winning. The second administrative source is the official website of the MGNREGA program, which gives information on employment provided, wages paid and expenditures made under the MGN- REGA for each GP, for each financial year, from April 2009 onwards. 9 We use these data to construct indicators of MGNREGA implementation for the financial year April 2009-March 2010, which covers the last year of the incumbent s mandate and the election month, and for the two financial years from April 2010 to March 2012, when the new Sarpanch is in power. In the first survey, 4541 households were interviewed in March-April 2010, i.e. one to two months after the elections in 240 GP (119 treatment GP and 121 control GP). The household survey included questions about households participation in MGNREGA. Each respondent was asked if she had wanted work during the past 12 months and whether or not she was provided employment by the administration of the GP. We use the respondents answers to corroborate official figures on MGNREGA employment during the incumbent mandate. 10 survey also included knowledge questions about MGNREGA rules and the role of the Sarpanch in MGNREGA. The second survey, implemented in October 2011, covered all Sarpanch candidates in the 240 GP from the household survey sample. The survey provided both a cross-check on the accuracy of the SEC data on candidates gender and caste and information on candidate education, profession, wealth and political career. In addition, we constructed a family tree for each candidate 9 http://nrega.nic.in 10 Official numbers are known to be inflated because of widespread corruption in the scheme (Niehaus and Sukhtankar, 2008; Imbert and Papp, 2011) The 11

to identify whether any family member was the incumbent, and more broadly to measure the political experience in the family. Finally, alongside the Sarpanch survey we also implemented an asset survey (in October 2011) in the same sample of GP. We sampled approximately 3200 assets (roads, irrigation canals, pavements, information center) built between April 2009 and March 2011 under MGNREGA from the official website. Once in the villages, enumerators tried to locate the infrastructures, and if found, to code their degree of completion. We use this survey to measure the number of assets completed by the incumbent (April 2009-March 2010) and the new Sarpanch (April 2010-March 2011). 3.2 Sample Depending on the outcome of interest, the delimitation of our sample varies. Some of our outcomes are measured for the whole sample of 382 GP: the number of candidates, by gender and caste and the performance of the new Sarpanch in implementing MGNREGA according to administrative sources. However, most of our outcomes are measured only for the 240 GP in which the three surveys of households, Sarpanch candidates and MGNREGA assets were implemented. Finally, because of rotating reservation for minorities, incumbents could only run in 64% of the sample GP. Hence, our sample is further reduced to 152 GP for outcomes such as the probability that the incumbent re-runs or incumbent s success in the elections. 4 Results 4.1 Empirical Strategy and Randomization Balance Given the randomization of both the reservation for women and the voter awareness campaign, the empirical strategy is straightforward. We estimate the following specification for most outcomes: y i = α + βr i + γ 1 T 1i + γ 2 T 2i + δ 1 T 1i R i + δ 2 T 2i R i + λ X i + ɛ i (1) where y i is an outcome of interest (e.g. number of candidates in GP i) R i is a dummy for having been reserved for women in 2005, T 1i is a dummy for receiving the general campaign, T 2i is a 12

dummy for receiving the gender campaign. We also allow for the additional interaction between women s reservation and exposure to general or gender treatment. X i is a vector of control variables, which include GP population, total number of voters, caste reservation (OBC, SC, ST) in 2010 elections, and reservation for women in 2000 elections. Table 1 reports village-level descriptive statistics, taken from the State Election Commission and from the 2001 census. Because of the randomization inherent both to our treatment and to the reservation policy, there are few significant differences between the villages 11. The only notable differences are that the gender campaign was more likely to happen in places that were reserved for women in 2000, and that there is a slight negative correlation between women reservation in 2005 and current reservation for SC. In the analysis below, we always include both the 2005 reservation dummy and the campaign dummies, and we also control for 2000 gender reservation and current reservation for OBC, SC and ST. Both the reservation and the general and gender campaigns were well implemented. All incumbents in GP reserved between 2005 and 2010 are female, while only 8% of incumbents in GP not reserved in 2005 were female. As we described above, the voters mobilization campaign was well implemented. An important question is how voters received the information disseminated in the campaign. The household survey data provides us with some indirect measures of thiswith questions on voters knowledge of MNREGA rules and of the role of the Sarpanch in implementing the scheme. on Table A.2 shows the effect of the campaign : awareness seems rather high (60-65%) in the control and does not seem to increase with the campaign. Optimism about the future benefits of development schemes in general to the village is also high (76%), and not significantly different in GP where the PEVAC was implemented. However, voters in treatment GP seem to be more optimistic about whether a good Sarpanch could make a difference, even in a corrupt environment. Hence the PEVAC may not have brought knowledge about what the Sarpanch is responsible for in MGNREGA but seems to have raised expectations about how much the Sarpanch could deliver. 11 The very significant negative correlation between reservation for women in 2000 and 2005 elections is due to the rotation of reservation decided by the State Election Commission. 13

4.2 Incumbency Advantage In Table 2 we start by examining the likelihood that incumbents ran for election, and their electoral success. Column (1) shows that the incumbent was less likely to run in both previously reserved GP and PEVAC GP. In GP with no PEVAC, incumbents from previously reserved GP were 31% less likely to run than their counterparts in un-reserved GP (their probability of running again is less than half of that of the incumbent from unreserved GP, 15% versus 46%). PEVACs were (perhaps) surprisingly effective at inducing incumbents to run: the decline due to the general campaign in the probability that the incumbent ran in GP that were not previously reserved is 27%! The campaign did not further discourage women incumbents from running (the interaction between campaign and previous reservation is positive and of similar magnitude as the negative main effect), which may be because incumbent women were not always perceived as established candidates. There is very little impact of the gender campaign on incumbents in GP that were not reserved. This is not particularly surprising as the campaign targeted voting along a gender dimension. The message was that women could be good Sarpanch too, not just men; but there was no focus on replacing a currently bad incumbent (as in the other show). Although not significant, in previously reserved places, the gender campaign may actually have slightly encouraged female incumbent to run again (the overall effect of the gender campaign in reserved areas is a positive 12 percentage point), which undoes half the effect of reservation. This would again make sense since the message was that women could be good Sarpanch, and it was therefore a relatively pro-incumbent message in places where the incumbent is a woman. These results are mirrored in the vote share results. Relative to a control group without reservation or campaign, where the incumbent gets on average a vote share of about 10 percentage point (this is not conditional on running, so an incumbent who does not run is assigned a vote share of zero), either reservation alone or campaign alone decrease the vote share received by the incumbent by more than 50%. As in the decision to run, the general treatment does not reduce the vote share for female incumbent and the gender campaign slightly helps them. The incumbent s vote share did go down as a result of the campaign but it is possible that this just resulted in a change of names. The incumbent could have just substituted a family 14

member for himself Querubin (2011) finds evidence of this in the Philippines. To be able to test for this in this context, we collected data on family relationships of each candidate with the past incumbent. We replace the variable did the incumbent run with did the incumbent or any member of his or her family run, and run the same regressions as for the incumbent (Table 2, columns 4 to 6). The impact of reservation on the decision to run and on vote share disappears almost entirely, suggesting that women were replaced by a (typically male) family member. 12 The impact of the campaign on the decision to run is reduced by more than a half, and once again the impacts on vote share and winning are much more muted. 4.3 Incumbent Selection Next, we examine whether incumbent performance influenced her decision of whether or not to re-run. In particular, we may expect greater accountability of incumbents (or incumbent dynasties, since citizens should be able to take into consideration the family strategies). This would imply that both the reservations and the anti-incumbent campaign should lead to a greater correlation between performance and the incumbent (and incumbent plus dynasty) vote share or decision to run. To test this hypothesis, we use survey interview on how many households received employment and whether people got jobs when they wanted them.we then run a regression where we include interactions of the performance index with the campaign: y i = α + βr i + γ 1 T 1i + γ 2 T 2i + δ 1 T 1i R i + δ 2 T 2i R i + ai i + br i I i + c 1 T 1i I i + c 2 T 2i I i + d 1 T 1i R i I i + d 2 T 2i R i I i + X i λ + ɛ i where I i is the performance index. The results are presented in Table 3. In GP that were neither reserved nor targeted by the PEVAC campaign, there is no positive correlation between the performance index and the decision to run or the vote share of the incumbent: the coefficient is even negative and significant for the index of employment 12 We will see below that reservations affects which dynasties get to continue to run and receive votes. 15

generated. However, we find that past reservation and the campaign seem to have increased political accountability: both in reserved GP and in GP where PEVAC occurred, there is a significant positive relationship between the decision to run and the employment and the asset index. Better incumbents are less affected by reservation and the campaign: moving from the average performance level to one standard deviation above the mean, the effect of the PEVAC on the probability of running for incumbents shrinks from -22% to virtually zero. In previously reserved places, it goes from -34% to -20%. Conversely, the probability that a bad incumbent with performance one standard deviation below the mean runs goes down to zero in GP previously reserved for women or where the campaign was held. We find similar results when looking at vote shares of incumbents. As we saw for the incumbent results, the impact of reservation and the campaign are not cumulative: the triple interaction between the index, reservation, and the general campaign is negative, offsetting one of the two positive interaction such that overall, there is no additional effect of the campaign on accountability in reserved GP. The results are the same, only stronger when we include both the incumbent and the incumbent s family (see Columns 4 to 6 of Table 3). Both previous reservation and the PEVAC campaign encouraged the family of the best incumbents to run. The probability of running increases from 54% to about 80% for family members of incumbents whose performance was one standard deviation above the mean and their average vote share goes up from 11 to 15%. The probability that there was a winner from an incumbent family also goes up significantly with incumbent s performance. 4.4 Candidate Entry Table 4 examines candidate entry excluding the incumbent. Column (1) shows that having been reserved or being exposed to a PEVAC lead to an increase in the number of candidates. Excluding the incumbent, roughly 7 candidates entered the election in GP which were not previously reserved for women. We observe roughly one additional candidate entering the fray in GP which were either previously reserved, or exposed to a PEVAC. There is no additional impact of getting a PEVAC in previously reserved GP. As Column 4 shows, half of the increase in the total number of candidates comes from candidates who decided to run less than 15 days before the elections. This seems a natural finding for the PEVAC, which indeed took place 16

between 21 and one day before the elections. For reservation, it may reflect uncertainty about the process of reservation itself: the reservation status of each GP was announced not more than a month before the elections. Turning to who was induced to enter by the treatments, we observe differences across the two treatments. Column (2) shows that more women entered in previously reserved GP (an increase of 48%). This is consistent with the results in Bhavnani (2009) and Beaman et al. (2009). 13 In contrast, as shown in Column (3) the PEVACs attracted a different group of traditional political outsiders: lower castes and tribal candidates (Other Backward Castes, Scheduled Castes and Scheduled Tribes). While political outsiders, these groups are not a minority: in the control group they represent the majority of candidates. There is more muted evidence that the combination of general treatment and a previous history of reservation increased entry by landless candidates (Column 5). Both reservation and PEVAC increased the number of literate candidates by about one (Column 6); however, they had no effect on the number of candidates with secondary education (results not shown here). This suggests that they attracted candidates with not more than primary education, as one would expect for members of disadvantaged social groups: female candidates in councils previously reserved for women and lower caste candidates where the PEVAC was implemented. A different measure of political advantage is political experience. While we find no evidence that PEVAC treatment increased entry by candidates who had contested the same position in 2005 (column 7) we do find that the general PEVAC increased entry by candidates who were previously elected for the lower position of ward councilor (column 9). The effect of reservation is more subtle. As Column 7 shows, (female) candidates who ran for a reserved seat were much less likely to run in 2010 than (mostly male) candidates who ran for an unreserved seat in 2005. However, once we take into account the whole family, family 13 To complete the replication of Beaman et al. (2009), in Appendix Table A.1, we reproduce the specification in Table 2 column 2, and display the effect of reservation in 2000: as in Beaman et al. (2009), we find that prior reservation also affects candidate entry (column 1) as well as success (columns 3). The two coefficients are jointly significant, and not significantly different from each other. The ever reserved dummy (reserved in 2000 or 2005), which is similar to the variable definition in their work has a robust and significant effect on entry and success in all specifications. 17

members of candidates who ran in previously reserved GP were not less likely to re-run in 2010 (Column 8). This suggests that challengers use the same family strategies as incumbents and replace female candidates by male once the reservation is removed. As shown in Table 5, prior reservation increases the vote share of female candidates. 14 The general campaign increases the vote share and the probability of winning of non-general candidates (Columns 3-4), of literate candidates (Columns 7-8) and of previous ward councillor (Columns 13-14). As before, the combination of reservation and PEVAC seems to have favored landless candidates, with a higher probability of winning. The effects of the gender treatment are noisily estimated, in most cases we cannot reject the null of no effect but the point estimates are sometimes large in magnitude. It seems a priori surprising that a campaign which had the same message as the general PEVAC, with an additional focus on the performance of women representatives do not seem to have had the same effect as the other PEVAC. One possible explanation is that the gender message overshadowed the general message, and that because of a lack of power, we are not able to characterize the effect it had on its own. To summarize, it seems that the two interventions which weakened the incumbent, both widened and changed the pool of candidates. The additional candidates who entered the race were more likely to come from disadvantaged groups: women in the case of reservation, lower caste in the case of PEVAC. They seem to have had a minimum level of education, and some political experience in the lower position of ward councilor. The changing nature of candidate entry raises the question of whether governance improved as a result of this campaign, to which we now turn. 4.5 Post Election Performance Here, we use the official statistics on employment to construct an employment index for each financial year since the elections (from 2010 to 2015) The results are presented in table 6. We find that in non-reserved GP, the general campaign led to a lower performance on the MGNREGA in terms of number of days provided. We find 14 Excluding the current incumbent the effect is marginally significant, it is significant when including the incumbent, and also when we considering 2000 and 2005 reservation together appendix table 1. 18

no impact on the number of households participating nor on the allocation of MGNREGA work to SC/ST households. There is no impact of past reservations on performance, and, in keeping with all the previous results, there is no impact of the campaign in previously reserved GP either (once again the interaction is of the opposite sign a magnitude suffcient to undo the negative effect of the campaign in previously unreserved areas). Thus, there is some evidence of short-run costs of broadening the representation base through the PEVAC campaign. This may be due to a lack of experience or political connections of the newly elected Sarpanch to get things done by the administration in charge of NREGA. 15 This finding needs to be interpreted with caution. For the post election period we only have official statistics of employment, and no household survey data. In the 2009-2010 period, for which we have both sources of information, the two measures are strongly correlated. However, it is widely recognized that there are significant gaps between official figures and household data on MGNREGA employment, due to inflation of person-days by corrupt officials (Niehaus and Sukhtankar, 2008; Imbert and Papp, 2011). 16 Hence we cannot exclude that some of the decrease in the official statistics reflects a decline in corruption, rather than a fall in actual employment. 4.6 Long term Electoral Outcomes We provide some evidence on the long term effects of our intervention by looking at electoral outcomes of 2010 candidates and elected leaders in the next election, in 2015. The results on incumbents are presented in Columns 1 and 2 of table 7. The low incumbency rate we observed in 2010 is also present in 2015. Less than a third of incumbents in our survey sample (68 out of 247) could run again in 2015. This is partly due to rotating women reservation: the state election commission mandated that one third of all GP should be reserved for women in 2015, but that GP should not be reserved for women for two consecutive elections. As a result, in our sample of GP who were not reserved for women in 2010, two thirds were reserved for women in 2015. Even in the few GP where incumbents can run the reelection rate is very low: only 4% of incumbents are reelected. We find no significant effect of previous reservation 15 When we run a regression for each year separately, the negative impact of the campaign disappears after three years, in 2012-13. 16 Comparisons across Indian states suggest that the gap is relatively small in Rajasthan (Imbert and Papp, 2011). 19

or the PEVAC, but the point estimates are large enough to bring the reelection rate to zero. When we extend the analysis to the incumbent and her family and extend the sample to GP where either the incumbent or her spouse could run, we find again very low probabilities for the incumbent family to run again (only 1.5%). There is little scope for past reservation or the PEVAC to have an effect. The electoral outcomes of 2010 candidates and their family are presented in Columns 3 and 4 of table 7. We find that in 9% of the GP one of 2010 candidates (in 20% of the GP a 2010 candidates and their family). These probabilities are lower in the GP which were previously reserved for women and in GP where we conducted the PEVAC, and the coefficients are large, but only one of them is significant at the 10% level. 5 Conclusion This paper studies the effect of two interventions which weakened the incumbent in the context of local elections in Rajasthan, India. We find that both reservation for women in the previous electoral cycle and a voter awareness campaign focused on the village head responsibilities decreased the probability that incumbents runs and wins the election. We measure performance of the incumbent in implementing a government program who provides employment to the poor and show that the worse incumbents were pushed out of the race. We find evidence that the incumbents fought back by letting another family member to run instead, but this did not help the worst performing incumbents. Both interventions attracted new candidates, coming from traditionally disadvantaged groups, women in the case of reservation and lower caste in the case of PEVAC. These candidates were more likely to be literate and to have some political experience acquired in the lower position of councilor. We provide some evidence that the newly elected leaders selected in constituencies which had the campaign performed worse in terms of employment generated under the same government program. We also find some weak evidence that the candidates who ran in 2010 after the PEVAC and their family were less likely to be elected in the 2015. This suggests that broader political representation may not imply an improvement in the quality of the candidate pool. 20

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Table 1: Summary Statistics Mean in Control Not WR in 2005 Difference in Control WR in 2005 Difference in General Treatment Not WR in 2005 Difference in Gender Treatment Not WR in 2005 Difference in General Treatment WR in 2005 Difference in Gender Treatment WR in 2005 CENSUS 2011 Number of villages 4.328-0.472* -0.0278 0.437-0.0500 0.0796 (2.242) (0.276) (0.364) (0.389) (0.515) (0.430) Population 5631-82.44 76.54 379.0 0.350-230.1 (1958) (251.3) (331.1) (354.2) (468.3) (391.0) Fraction SC Population 0.222 0.00219-0.00607 0.0452** -0.0364-0.0129 (0.121) (0.0155) (0.0204) (0.0218) (0.0289) (0.0241) Fraction ST Population 0.105 0.0270 0.0382-0.00192-0.0624 0.0383 (0.188) (0.0253) (0.0334) (0.0357) (0.0472) (0.0394) Fraction Literate Population 0.551 0.00383 0.0107 0.00939-0.00363-0.0147 (0.0651) (0.00852) (0.0112) (0.0120) (0.0159) (0.0133) Fraction Cultivators 0.180 0.00355 0.00190-0.0174-0.00509-0.00384 (0.0606) (0.00780) (0.0103) (0.0110) (0.0145) (0.0121) Fraction Agricultural Laborers 0.0622-0.0104* -0.00758 0.00760-0.00812 0.000732 Fraction of villages with access to drinking water Fraction of villages connected to a paved road Fraction of villages with (0.0417) (0.00532) (0.00701) (0.00749) (0.00991) (0.00827) 0.931-0.0358* 0.0167 0.0211-0.00443-0.0771** (0.151) (0.0211) (0.0278) (0.0297) (0.0393) (0.0328) 1.574-0.0450 0.0477 0.0308-0.00917 0.00600 (0.323) (0.0411) (0.0541) (0.0579) (0.0765) (0.0639) 0.930-0.0405* 0.00835 0.0235 0.00682-0.0505 (0.151) (0.0224) (0.0295) (0.0316) (0.0418) (0.0349) access to power supply STATE ELECTION COMMISSION 2010 Number of voters 2913 103.3 17.02 199.1 385.9-119.3 (1036) (127.8) (168.4) (180.1) (238.1) (198.8) Reserved for women in 2000 0.444-0.420*** -0.0194 0.203** -0.389*** -0.333*** (0.498) (0.0562) (0.0741) (0.0793) (0.105) (0.0875) Reserved for OBC in 2010 0.161-0.0165 0.0389 0.104-0.0500-0.124 (0.369) (0.0486) (0.0640) (0.0684) (0.0905) (0.0755) Reserved for SC in 2010 0.250-0.0934* 0.0250 0.0147 0.0278-0.0648 (0.434) (0.0560) (0.0738) (0.0789) (0.104) (0.0871) Reserved for ST in 2010 0.100 0.0566 0-0.0118-0.100 0.0481 (0.301) (0.0416) (0.0548) (0.0586) (0.0774) (0.0647) Incumbent can run in 2010 0.633 0.0655-0.133-0.0451 0.0889 0.107 (0.483) (0.0636) (0.0837) (0.0896) (0.118) (0.0989) Number of GP 180 83 40 18 34 27 Notes: 1. Standard deviation below in parenthesis. 2. Stars denote the significance level of the difference * for 10%, ** for 5% and *** for 1% significance. 23

Table 2: Incumbent success Incumbent Incumbent or family Runs Voteshare Wins Runs Voteshare 1 2 3 4 5 Women Reserved in 2005 (WR) -0.370*** -10.53*** -0.0490-0.0953-5.451 (0.107) (2.694) (0.0549) (0.122) (3.300) General treatment -0.287** -7.561*** -0.0513-0.0580-4.494 (0.112) (2.859) (0.0575) (0.127) (3.503) Gender treatment -0.201* -1.813 0.0579-0.0743-0.959 (0.120) (3.013) (0.0615) (0.136) (3.691) General treatment*wr 0.236 6.185 0.00740-0.167-3.261 (0.178) (4.589) (0.0914) (0.203) (5.622) Gender treatment*wr 0.339* 7.040-0.0113 0.149 9.414* (0.173) (4.333) (0.0886) (0.196) (5.308) Mean in Control (not WR 2005) 0.462 10.10 0.0577 0.538 11.55 Mean in Control ( WR 2005) 0.148 2.505 0.0370 0.481 8.652 Observations 152 149 152 152 149 District FE Yes Yes Yes Yes Yes GP Controls No No No No No NOTES: 1.The sample includes all 152 GPs which were surveyed and where the incumbent could 2010. Information on voteshare is missing for three GPs. 2.GP controls include GP population, nu villages, share of SC in GP population, share of ST in GP population, literacy rate, Gender reservat of GP for 2000, Caste (OBC SC and ST) reservation status for 2010. 3.Columns 2 and 5 are missing observations since vote data does not exist for these GPs.

Table 3: Incumbent Success Depending on Incumbent Performance Incumbent Incumbent or family member Runs Voteshare Wins Runs Voteshare Wins 1 2 3 4 5 6 NREGA Employment Index -0.113* -3.595** -0.042-0.084-3.498* -0.056 [0.063] [1.585] [0.033] [0.071] [1.944] [0.041] WR in 2005-0.342*** -10.114*** -0.038-0.034-4.167-0.049 [0.107] [2.701] [0.056] [0.120] [3.312] [0.070] General treatment -0.234** -6.423** -0.062 0.023-2.857 0.054 [0.113] [2.931] [0.059] [0.127] [3.594] [0.074] Gender treatment -0.221* -2.227 0.075-0.083-1.267 0.067 [0.119] [2.994] [0.062] [0.133] [3.672] [0.078] General treatment*wr 0.174 4.644 0.002-0.295-6.074-0.126 [0.179] [4.627] [0.093] [0.200] [5.674] [0.117] Gender treatment*wr 0.373** 8.139* -0.039 0.091 8.792 0.069 [0.177] [4.442] [0.092] [0.197] [5.446] [0.115] WR in 2005*Index 0.218* 5.110 0.093 0.254* 8.754** 0.092 [0.130] [3.273] [0.068] [0.146] [4.014] [0.085] General treatment*index 0.364*** 8.632*** 0.014 0.450*** 10.035** 0.138 [0.128] [3.275] [0.067] [0.143] [4.016] [0.083] Gender treatment*index 0.054 2.238-0.107-0.203-0.250-0.106 [0.148] [3.711] [0.077] [0.165] [4.550] [0.096] General treatment*wr*index -0.618*** -12.984** -0.076-0.588** -17.369** -0.182 [0.222] [5.718] [0.115] [0.247] [7.011] [0.145] Gender treatment*wr*index -0.285-7.129 0.044 0.081-6.215 0.048 [0.221] [5.551] [0.115] [0.247] [6.807] [0.144] Observations 152 149 152 152 149 152 District FE Yes Yes Yes Yes Yes Yes GP controls Yes Yes Yes Yes Yes Yes Notes: 1.The sample includes all 152 GPs which were surveyed and where the incumbent could re-run in 2010. Information on asset quality is missing in one GP and voteshare is not observed for three GPs. 2.Performance indexes are based on standardized values of various measures of MG-NREGS implementation. The "Employment" index is composed of the fraction of household who worked in MGNREGS in the last 12 months and the fraction of men and women who would have liked to work in MG-NREGS in the last 12 months and could get work (household survey). 3.GP controls include GP population, number of villages, share of SC in GP population, share of ST in GP population, literacy rate, Gender reservation status of GP for 2000, Caste (OBC SC and ST) reservation status for 2010. 4.The specification is described in Section 4.3

Table 4: Challengers entry Number of candidates Total % Female % Lower Caste % Decided less than 15 days before % Landless 1 2 3 4 5 Women Reserved in 2005 (WR) 1.091* 0.0126 0.0378 0.0818** -0.0191 (0.575) (0.0275) (0.0340) (0.0385) (0.0295) General treatment 1.174* 0.0163 0.0906** 0.0779** -0.0293 (0.702) (0.0337) (0.0415) (0.0362) (0.0277) Gender treatment -0.531 0.00459 0.0644-0.00387-0.0265 (0.763) (0.0366) (0.0451) (0.0393) (0.0301) General treatment*wr -0.605-0.0139 0.0402-0.0681 0.110** (1.267) (0.0607) (0.0749) (0.0652) (0.0499) Gender treatment*wr -0.773-0.00650-0.126* -0.0250 0.0889* (1.176) (0.0564) (0.0696) (0.0616) (0.0472) Mean in Control not WR in 2005 7.139 0.126 0.787 0.175 0.109 Mean in Control ( WR 2005) 7.139 0.112 0.783 0.248 0.0662 Observations 382 382 382 240 240 District FE Yes Yes Yes Yes Yes GP controls Yes Yes Yes Yes Yes Number of candidates % Literate % Ran for sarpanch before % Any family member ran for sarpanch before % Any family % Elected as member wardpanch before wardpanch before 6 7 8 9 10 Women Reserved in 2005 (WR) 0.0843* -0.00715 0.0457 0.0270-0.0902** (0.0429) (0.0306) (0.0351) (0.0251) (0.0397) General treatment 0.0963** -0.0121-0.00476 0.0595** 0.0148 (0.0403) (0.0287) (0.0330) (0.0236) (0.0373) Gender treatment 0.0185-0.0162 0.0218 0.0393-0.0305 (0.0437) (0.0312) (0.0358) (0.0256) (0.0405) General treatment*wr -0.0803-0.0485-0.0228-0.0646-0.0149 (0.0726) (0.0518) (0.0594) (0.0424) (0.0672) Gender treatment*wr -0.0261-0.0141-0.00362-0.00123 0.138** (0.0686) (0.0489) (0.0562) (0.0401) (0.0635) Mean in Control not WR in 2005 0.650 0.128 0.173 0.0595 0.335 Mean in Control ( WR 2005) 0.762 0.135 0.235 0.0902 0.260 Observations 240 240 240 240 240 District FE Yes Yes Yes Yes Yes GP controls Yes Yes Yes Yes Yes NOTES: 1.The total number of candidates by caste and gender is available for all 382 GPs. The other characteristics of the candidates are only known for the survey sample (240 GPs). 2.GP controls include GP population, number of villages, share of SC in GP population, share of ST in GP population, literacy rate, Gender reservation status of GP for 2000, Caste (OBC SC and ST) reservation status for 2010. 3.The specification is described in Section 4.1.

Table 5: Electoral success of weaker challengers Type of candidate Female Lower Caste Decided Late Landless Voteshare Wins Voteshare Wins Voteshare Wins Voteshare Wins 1 2 3 4 5 6 7 8 Women Reserved in 2005 (WR) 4.147 0.0482 2.887-0.0206 6.051-0.0432-2.813-0.0910* (3.038) (0.0500) (3.608) (0.0493) (4.589) (0.0863) (3.217) (0.0525) General treatment -0.0410 0.0290 11.39** 0.122** 11.74*** 0.171** -0.840-0.0660 (3.803) (0.0611) (4.516) (0.0602) (4.389) (0.0811) (3.077) (0.0493) Gender treatment -3.599-0.0269 5.378 0.0488 1.121 0.0981-3.878-0.0105 (3.995) (0.0664) (4.745) (0.0654) (4.623) (0.0880) (3.241) (0.0535) General treatment*wr -1.911-0.0371-1.557 0.00680-6.330-0.195 8.446 0.159* (6.836) (0.110) (8.119) (0.109) (7.899) (0.146) (5.537) (0.0888) Gender treatment*wr -0.0228-0.0403-11.96-0.117 0.843 0.0606 14.64*** 0.171** (6.172) (0.102) (7.331) (0.101) (7.279) (0.138) (5.103) (0.0839) Mean in Control not WR in 2005 12.89 0.144 78.70 0.822 15.72 0.193 9.066 0.0964 Mean in Control WR in 2005 13.73 0.157 77.10 0.771 21.82 0.158 3 0 Observations 373 382 373 382 234 240 234 240 District FE Yes Yes Yes Yes Yes Yes Yes Yes GP Controls Yes Yes Yes Yes Yes Yes Yes Yes Type of candidate Literate Ran for sarpanch before Any family member ran for sarpanch before Elected as wardpanch before Voteshare Wins Voteshare Wins Voteshare Wins Voteshare Wins 9 10 11 12 13 14 15 16 Women Reserved in 2005 (WR) 5.854 0.00280-2.247-0.0314 6.794 0.0551-1.206-0.0384 (4.920) (0.0859) (4.154) (0.0771) (4.666) (0.0910) (3.186) (0.0563) General treatment 9.214* 0.138* -2.481-0.0306-3.700-0.0457 10.90*** 0.154*** (4.706) (0.0807) (3.973) (0.0725) (4.463) (0.0855) (3.047) (0.0529) Gender treatment -0.698-0.0204-3.650-0.0932-1.228-0.115 4.910 0.0939 (4.956) (0.0876) (4.185) (0.0786) (4.700) (0.0927) (3.209) (0.0574) General treatment*wr -1.458 0.0277-8.957-0.172-3.712-0.122-8.218-0.160* (8.468) (0.145) (7.150) (0.131) (8.031) (0.154) (5.483) (0.0952) Gender treatment*wr 3.187 0.197 0.0174 0.0104 1.645 0.173 0.434-0.0246 (7.804) (0.137) (6.590) (0.123) (7.401) (0.145) (5.053) (0.0900) Mean in Control not WR in 2005 66.04 0.675 18 0.229 23.84 0.337 6.702 0.0482 Mean in Control WR in 2005 76.13 0.737 18.55 0.211 33.15 0.395 5.981 0.0526 Observations 234 240 234 240 234 240 234 240 District FE Yes Yes Yes Yes Yes Yes Yes Yes GP Controls Yes Yes Yes Yes Yes Yes Yes Yes NOTES: 1.The total number of candidates by caste and gender is available for all 382 GPs. The other characteristics of the candidates are only known for the survey sample (240 GPs). 2."Voteshare" columns have less observations since vote data does not exist for some GPs. 3. GP controls include GP population, number of villages, share of SC in GP population, share of ST in GP population, literacy rate, Gender reservation status of GP for 2000, Caste (OBC SC and ST) reservation status for 2010. 4.The specification is described in Section 4.1

Table 6: Effect on Performance of the newly elected Sarpanch Household NREGA participation NREGA days per household Share of NREGA days to SC/ST Households First year 2010-11 Average 2010-15 First year 2010-11 Average 2010-15 First year 2010-11 Average 2010-15 1 2 3 4 5 6 Women Reserved in 2005 (WR) 0.004 0.010-0.791 0.222 0.003 0.009 (0.030) (0.022) (1.653) (1.128) (0.018) (0.019) General treatment -0.049-0.025-4.345** -2.290* 0.006 0.009 (0.037) (0.027) (2.010) (1.371) (0.021) (0.023) Gender treatment -0.028 0.025-0.410 1.753 0.008-0.021 (0.040) (0.029) (2.178) (1.486) (0.023) (0.025) General treatment*wr 0.129* 0.056 11.089*** 5.180** -0.017-0.032 (0.066) (0.049) (3.624) (2.473) (0.038) (0.041) Gender treatment*wr 0.039-0.006 0.016-1.675 0.002 0.092** (0.061) (0.045) (3.369) (2.299) (0.036) (0.039) Mean in Control in Women Unreserved 2005 0.430 0.320 15.45 11.55 0.360 0.369 Mean in Control in Women Reserved 2005 0.488 0.371 16.61 13.04 0.372 0.385 Observations 382 382 379 380 379 380 District FE Yes Yes Yes Yes Yes Yes GP Controls Yes Yes Yes Yes Yes Yes NOTES: 1.GP controls include GP population, number of villages, share of SC in GP population, share of ST in GP population, literacy rate, Gender reservation status of GP for 2000, Caste (OBC SC and ST) reservation status for 2010. 2.We also control for the level of the index pre elections. 3. In Column 1 and 2 the dependent variable is the number of participating household per year (official website) divided by the total number of households (2011 Census). In Column 3 and 4 the dependent variable is the number of NREGA days per year (official website) divided by the total number of households (2011 Census). In Column 4 and 5 the dependent variable is the number of NREGA days given to SC/ST households per year (official website) divided by the total number of NREGA days (official website). 4. The specification is described in Section 4.1

Table 7: Effect on long term electoral outcomes Sarpanch elected in 2015 is: Incumbent Incumbent or 2010 Candidate 2010 Candidate family or family 1 2 3 4 Women Reserved in 2005 (WR) -0.0536-0.0194-0.0346-0.0782 (0.0489) (0.0229) (0.0538) (0.0732) General treatment -0.0745 0.0148-0.0440-0.130* (0.0448) (0.0205) (0.0506) (0.0689) Gender treatment -0.0571-0.0156 0.00759-0.0883 (0.0673) (0.0228) (0.0547) (0.0745) General treatment*wr 0.0669-0.0191 0.0313 0.113 (0.0780) (0.0368) (0.0904) (0.123) Gender treatment*wr 0.0573 0.0157-0.0549 0.142 (0.0857) (0.0358) (0.0858) (0.117) Mean in Control (not WR 2005) 0.0435 0.0149 0.0941 0.200 Mean in Control (WR 2005) 0 0 0.0769 0.128 Observations 68 204 247 247 District FE Yes Yes Yes Yes GP Controls Yes Yes Yes Yes NOTES: 1. In Column 1 the sample includes only the 68 GP which were surveyed and where the incumbent could re-run. In Column 2 the sample includes the 204 GP which were surveyed and where the incumbent or her spouse could re-run. In Column 3 and 4 the sample includes the sample includes all 247 GPs which were surveyed. 2.GP controls include GP population, number of villages, share of SC in GP population, share of ST in GP population, literacy rate, Gender reservation status of GP for 2000, Caste (OBC SC and ST) reservation status for 2010. 3. In Column 1 and 2 the dependent variable is a dummy variable equal to one if one of the 2010 candidates (or a member of her family) was elected sarpanch in 2015. In Column 3 and 4 the dependent variable is a dummy variable equal to one if the incumbent sarpanch (or a member of her family) was elected sarpanch in 2015. 4. The specification is described in Section 4.1

Table A.1: Previous Reservation and Women Success in Elections All female candidates Runs Voteshare Wins 1 2 3 4 5 6 Women Reserved in 2005 0.434** 6.396** 0.0531 (0.197) (2.790) (0.0436) Women Reserved in 2000 0.231 4.933* 0.0659 (0.196) (2.795) (0.0435) General treatment 0.122 0.129-2.053-1.914 0.00520 0.00605 (0.234) (0.234) (3.398) (3.385) (0.0520) (0.0518) Gender treatment -0.100-0.0937-2.991-2.962-0.0334-0.0341 (0.232) (0.231) (3.264) (3.240) (0.0515) (0.0511) WR in 2005 OR 2000 0.387** 6.903*** 0.0758* (0.175) (2.485) (0.0388) Mean in Not WR 2005 nor 2000 0.735 0.735 9.396 9.396 0.103 0.103 Joint significance WR 2005 and 2000 0.0866 0.0509 0.263 Observations 382 382 373 373 382 382 R-squared 0.040 0.039 0.043 0.047 0.030 0.033 District FE Yes Yes Yes Yes Yes Yes GP Controls Yes Yes Yes Yes Yes Yes Female challengers only Runs Voteshare Wins 7 8 9 10 11 12 Women Reserved in 2005 0.334* 4.200 0.0398 (0.193) (2.626) (0.0430) Women Reserved in 2000 0.242 5.342** 0.0684 (0.192) (2.631) (0.0429) General treatment 0.143 0.148-1.239-1.176 0.00841 0.00898 (0.230) (0.229) (3.198) (3.188) (0.0512) (0.0511) Gender treatment -0.130-0.125-3.721-3.734-0.0446-0.0455 (0.227) (0.226) (3.072) (3.052) (0.0507) (0.0504) WR in 2005 OR 2000 0.334* 5.804** 0.0690* (0.172) (2.340) (0.0383) Mean in Not WR 2005 nor 2000 0.728 0.728 9.283 9.283 0.103 0.103 Joint significance WR 2005 and 2000 0.191 0.0933 0.272 Observations 382 382 373 373 382 382 R-squared 0.037 0.039 0.041 0.045 0.029 0.031 District FE Yes Yes Yes Yes Yes Yes GP Controls Yes Yes Yes Yes Yes Yes NOTES: 1. The sample includes all 382 GPs not reserved for women in 2010 elections. 2.GP controls include GP population, literacy rate,, number of registered voters, Gender reservation status of GP for 2000, Caste (OBC SC and ST) reservation status for 2010. 3."Voteshare" columns are missing 9 observations since vote data does not exist for these GPs. 4.The specification is described in Section 4.1

Table A.2: Knowledge and Perceptions of MGNREGA Knowledge of Rating of Optimism about NREGA Rules Sarpanch Role NREGA Public Good Development Good Sarpanch Implementation Provision programs 1 2 3 4 5 6 Women reservation in 2005 0.00635 0.00180 0.00869 0.00228-0.00299-0.0526 (0.0415) (0.0429) (0.0687) (0.0555) (0.0428) (0.0827) General treatment -0.0460-0.0180-0.00338 0.0435-0.0299 0.0334 (0.0450) (0.0374) (0.0522) (0.0623) (0.0400) (0.0624) Gender treatment 0.0310 0.0452 0.0175 0.126** 0.0379 0.121* (0.0453) (0.0528) (0.0591) (0.0637) (0.0434) (0.0680) General Treatment*WR in 2005 0.0356-0.0408-0.0564-0.107-0.000611 0.181* (0.0732) (0.0797) (0.101) (0.0980) (0.0762) (0.108) Gender Treatment*WR in 2005 0.0533-0.0323-0.0660-0.0680-0.0127-0.0809 (0.0693) (0.0763) (0.105) (0.0992) (0.0667) (0.125) Observations 9,788 9,788 9,783 9,770 9,788 9,788 District FE Yes Yes Yes Yes Yes Yes Controls Yes Yes Yes Yes Yes Yes Notes: 1. The dependent variables are described below. They are all z-score standardized to have mean zero an standard deviation one in control GP not WR in 2005, 2. Individual controls include gender, age, years of education, literacy, and a dummy variable for individual participation in NREGA. 3. Household controls include a dummy variable for Below Poverty Line status, a dummy variable for whether the household owns land, a dummy variable for household NREGA participation, a set of dummy variables for religion, and a set of dummy variables for caste. 4. GP controls are GP population, number of registered voters, and caste (OBC, SC and ST) reservation status for 2005. Dependent variables:1. Knowledge of NREGA Rules: Average of correct answers to questions about the NREGA daily wage and the maximum number of NREGA days per household. 2. Knowledge of Sarpanch Role: Average of correct answers to questions about the Sarpanch role in registering households, providing employment and checking workers payments. 3. Rating of NREGA implementation: "How would you rate NREGA implementation in your village?" Possible answers were "Very good/good/bad/very bad" 4. Rating of public good provision: "On a scale of 1 to 10, how satisfied are you with the provision of the following public goods in your village?". Respondents were asked successively about water, school and road. 5 Optimism about Development Programs: Positive answer to the question "Do you think government programs will help your village develop in the next five years?". 6. Optimism about Good Sarpanch: Negative answer to the question "Do you agree with people who say that if the system is corrupt a good Sarpanch cannot do a difference?".

Table A.3: Determinants of Attendance to the Shows Log Total Attendance Log Female Attendance 1 2 3 4 Number of shows 0.156* 0.216*** 0.210** 0.261*** (0.0835) (0.0755) (0.0994) (0.0903) Days to the elections -0.00834-0.00275-0.00891-0.00233 (0.0116) (0.0105) (0.0138) (0.0126) Days spent in the Panchayat -0.0462-0.105 0.148 0.0583 (0.195) (0.175) (0.234) (0.212) Gender treatment 0.0614 0.0778 0.105 0.154 (0.186) (0.167) (0.221) (0.201) WR in 2005 OR in 2000 0.198 0.129 0.431** 0.340** (0.145) (0.136) (0.173) (0.163) Gender T * WR in 2005 OR 2000-0.0881-0.0117-0.268-0.237 (0.223) (0.201) (0.266) (0.242) OBC reservation in 2010-0.0748-0.0841 0.307* 0.227 (0.139) (0.129) (0.166) (0.157) SC reservation in 2010-0.121-0.120-0.223-0.207 (0.119) (0.108) (0.142) (0.131) ST reservation in 2010-0.224-0.278-0.544** -0.610*** (0.194) (0.173) (0.223) (0.201) Number of villages in the GP -0.00807-0.0125-0.0277-0.0324 (0.0333) (0.0300) (0.0399) (0.0363) Log Total population in the GP 0.121 0.166-0.264-0.286 (0.241) (0.216) (0.282) (0.256) Log SC population in the GP -0.0376-0.0678 0.00465-0.00969 (0.0847) (0.0797) (0.101) (0.0960) Log ST population in the GP -0.00746 0.0245-0.00940 0.0493 (0.0368) (0.0362) (0.0441) (0.0438) No ST population in the GP -0.290-0.132-0.334-0.0417 (0.229) (0.223) (0.274) (0.269) % of HH who worked in NREGA -0.214-0.317-0.0738-0.151 (0.233) (0.209) (0.279) (0.253) Literacy rate 0.796* 0.428 1.114** 0.549 (0.451) (0.467) (0.541) (0.566) Observations 117 117 118 118 Monitor FE No Yes No Yes Notes: Information on total attendance is missing for two treatment Panchayat, and infomation on female attendance is missing for one treatment Panchayat. The number of shows, number of days to the elections, the number of days spent by the campaign teams in each Panchayat come from monitor reports. "No St population in the GP" is a dummy variable which takes the value one if there was no ST population in the GP. In that case the variable "Log ST population" was set to zero. The percentage of households who worked in NREGA in the last 12 months and the literacy rate are estimates based on household survey data.

Figure A.1: Sample of Calendar from the General Campaign 33

Figure A.2: Sample of Calendar from the Gender Campaign 34