Adam Michael Auerbach and Tarig Thachil trait (and candidate)is more desirable than another. Census of India).Second,Jaipur and Bhopal share sim- Second,such treatments are abstract,raising the con ilarities that facilitate their joint study:both are state struct validity concerns we sought to avoid.Residents capitals,comparably sized,and situated within India's cannot directly observe a leader's connectivity.and "Hindi belt."Third,the authors have conducted a com- leaders have every incentive to exaggerate their con- bined three years of fieldwork in urban India,including nections.Residents must thus infer a broker's poten- in Jaipur and Bhopal.Prior fieldwork was crucial for tial connectivity from observable traits.27 We therefore the design and execution of the survey. prefer a nonevaluative and observable measure of con- We administered our conjoint survey experiment nectivity,such as occupation. during the summer of 2015 to 2,199 households across We assign leaders one of three broad occupational 110 slums,60 in Bhopal(Figure S.4),and 50 in Jaipur types,each of which indicates an increasing level of (Figure S.5).We first collected recent official slum lists bureaucratic connectivity.The first are occupations in each city.30 The category of slum includes housing entirely contained within the slum,which provide conditions that vary in their origins and formality.We little scope for external connections.Ubiquitous ex- focus on squatter settlements:spontaneous areas con- amples are owners of informal shops catering to resi- structed by residents in an unsanctioned,unplanned dents.Our manipulations include three such jobs:cor- fashion.We isolated a sampling frame of 307 such set- ner shop owner,tea stall owner,and cigarette-paan28 tlements from the wider slum list through intensive stand owner. field visits.interviews,and examinations of satellite im- The second are occupations located outside the slum, ages.Settlements were then selected through multi- but not explicitly connected to municipal authorities stage random sampling stratified on population and ge- Three common examples we selected were:street ven- ographic area. dor,auto rickshaw driver,and unskilled house painter. We sampled 20 households per slum by generating These professions require residents to circulate outside Google Earth satellite images for each settlement(Fig- the slum,providing greater opportunities to gather in- ure S.3).Using a digital drawing program,we measured 4号元 formation about developments within the city than"in- pixel widths and lengths of each image.We then ran- ternal"professions.These jobs indicate an intermedi- domly selected width and length pixel points to mark ate level of connectivity. on each image.New points were selected if a point fell Finally,we include high connectivity occupations on a vacant area or outside the settlement. that are external to the slum and directly connected to We trained team leaders to navigate the satellite municipal authorities.For example,leaders who work images and place enumerators at their randomly se- within municipal offices could plausibly be seen as hav- lected households.If respondents were unavailable or ing greater knowledge of how to get demands met than unwilling,enumerators approached an adjacent house. those without these direct ties.As one interviewee told Seventy-three percent of initially selected households us: were interviewed (only 9%were refusals).The survey was conducted in the afternoon and early evening to Even if a man is just a chowkidar [security guard]at the balance access to individuals who stay at home with municipal office,his bosses will be important people he those working outside the settlement.Enumerators sees everyday.So if he asks them to make sure the mu- selected individuals within each household based on nicipality sends sweepers to clean our gutters,won't it be more likely they listen to him?29 availability and an eye to ensuring gender balance.At least one author and a supervisor accompanied the sur- vey teams in the field for the duration of the study. Poor slum residents are unlikely to hold significant positions within the municipal government,but can Table 1 provides some descriptive statistics regarding our survey sample. work in low-level jobs within these offices.Our ma- nipulations include three such jobs:clerk(chaprasi), sweeper (safai karamchari),and security guard in the QUALITATIVE VIGNETTE municipal office. To briefly show how ethnography informed our the- ory and experiment design,we present an ethnographic Research Sites and Survey Sampling narrative from Saraswati,a slum in Jaipur.This vignette We conducted our study in the north Indian cities of illustrates the relevance of particular attributes and Jaipur and Bhopal for several reasons.First,most In- their observable indicators,local processes of compet- itive leadership selection,and the importance of resi- dian slum residents live in an expanding number of dent agency within such procedures. smaller cities spread throughout the country,not in the megacities of Bangalore,Delhi,and Mumbai(2011 Migrants first settled Saraswati in the late 1970s to work as miners in nearby stone quarries.The popu- lation of the slum now stands at 2,600 residents,and 27 For similar reasons.our capability treatment is not an evaluative is diverse in caste and regional terms.Saraswati is lo- L "Candidate B has high/medium/low capability,but based on an ob- cated on land administered by the Forest Department, servable trait clients use to infer capability.See Section S.3 for a dis- cussion on the indicators used to tap our concepts of capability and connectivity. 28Pan is a popular stimulant combining betel leaves and areca nuts 30 These lists include nonrecognized slums,avoiding coverage bias 29 Field notes,Jaipur,June 272015. from limiting sampling to officially recognized slums. 782Adam Michael Auerbach and Tariq Thachil trait (and candidate) is more desirable than another. Second, such treatments are abstract, raising the con￾struct validity concerns we sought to avoid. Residents cannot directly observe a leader’s connectivity, and leaders have every incentive to exaggerate their con￾nections. Residents must thus infer a broker’s poten￾tial connectivity from observable traits.27 We therefore prefer a nonevaluative and observable measure of con￾nectivity, such as occupation. We assign leaders one of three broad occupational types, each of which indicates an increasing level of bureaucratic connectivity. The first are occupations entirely contained within the slum, which provide little scope for external connections. Ubiquitous ex￾amples are owners of informal shops catering to resi￾dents. Our manipulations include three such jobs: cor￾ner shop owner, tea stall owner, and cigarette-paan28 stand owner. The second are occupations located outside the slum, but not explicitly connected to municipal authorities. Three common examples we selected were: street ven￾dor, auto rickshaw driver, and unskilled house painter. These professions require residents to circulate outside the slum, providing greater opportunities to gather in￾formation about developments within the city than “in￾ternal” professions. These jobs indicate an intermedi￾ate level of connectivity. Finally, we include high connectivity occupations that are external to the slum and directly connected to municipal authorities. For example, leaders who work within municipal offices could plausibly be seen as hav￾ing greater knowledge of how to get demands met than those without these direct ties. As one interviewee told us: Even if a man is just a chowkidar [security guard] at the municipal office, his bosses will be important people he sees everyday. So if he asks them to make sure the mu￾nicipality sends sweepers to clean our gutters, won’t it be more likely they listen to him?29 Poor slum residents are unlikely to hold significant positions within the municipal government, but can work in low-level jobs within these offices. Our ma￾nipulations include three such jobs: clerk (chaprasi), sweeper (safai karamchari), and security guard in the municipal office. Research Sites and Survey Sampling We conducted our study in the north Indian cities of Jaipur and Bhopal for several reasons. First, most In￾dian slum residents live in an expanding number of smaller cities spread throughout the country, not in the megacities of Bangalore, Delhi, and Mumbai (2011 27 For similar reasons, our capability treatment is not an evaluative “Candidate B has high/medium/low capability,” but based on an ob￾servable trait clients use to infer capability. See Section S.3 for a dis￾cussion on the indicators used to tap our concepts of capability and connectivity. 28 Paan is a popular stimulant combining betel leaves and areca nuts. 29 Field notes, Jaipur, June 27, 2015. Census of India). Second, Jaipur and Bhopal share sim￾ilarities that facilitate their joint study: both are state capitals, comparably sized, and situated within India’s “Hindi belt.” Third, the authors have conducted a com￾bined three years of fieldwork in urban India,including in Jaipur and Bhopal. Prior fieldwork was crucial for the design and execution of the survey. We administered our conjoint survey experiment during the summer of 2015 to 2,199 households across 110 slums, 60 in Bhopal (Figure S.4), and 50 in Jaipur (Figure S.5). We first collected recent official slum lists in each city.30 The category of slum includes housing conditions that vary in their origins and formality. We focus on squatter settlements: spontaneous areas con￾structed by residents in an unsanctioned, unplanned fashion. We isolated a sampling frame of 307 such set￾tlements from the wider slum list through intensive field visits, interviews, and examinations of satellite im￾ages. Settlements were then selected through multi￾stage random sampling stratified on population and ge￾ographic area. We sampled 20 households per slum by generating Google Earth satellite images for each settlement (Fig￾ure S.3). Using a digital drawing program, we measured pixel widths and lengths of each image. We then ran￾domly selected width and length pixel points to mark on each image. New points were selected if a point fell on a vacant area or outside the settlement. We trained team leaders to navigate the satellite images and place enumerators at their randomly se￾lected households. If respondents were unavailable or unwilling, enumerators approached an adjacent house. Seventy-three percent of initially selected households were interviewed (only 9% were refusals). The survey was conducted in the afternoon and early evening to balance access to individuals who stay at home with those working outside the settlement. Enumerators selected individuals within each household based on availability and an eye to ensuring gender balance. At least one author and a supervisor accompanied the sur￾vey teams in the field for the duration of the study. Table 1 provides some descriptive statistics regarding our survey sample. QUALITATIVE VIGNETTE To briefly show how ethnography informed our the￾ory and experiment design, we present an ethnographic narrative from Saraswati, a slum in Jaipur.This vignette illustrates the relevance of particular attributes and their observable indicators, local processes of compet￾itive leadership selection, and the importance of resi￾dent agency within such procedures. Migrants first settled Saraswati in the late 1970s to work as miners in nearby stone quarries. The popu￾lation of the slum now stands at 2,600 residents, and is diverse in caste and regional terms. Saraswati is lo￾cated on land administered by the Forest Department, 30 These lists include nonrecognized slums, avoiding coverage bias from limiting sampling to officially recognized slums. 782 Downloaded from https://www.cambridge.org/core. Shanghai JiaoTong University, on 26 Oct 2018 at 03:53:05, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S000305541800028X