American Political Science Review (2018)112.4,775-791 doi:10.1017/S000305541800028X American Political Science Association 2018 How Clients Select Brokers:Competition and Choice in India's Slums ADAM MICHAEL AUERBACH American University TARIO THACHIL Vanderbilt University onventional models of clientelism often assume poor voters have little or no choice over which lo- cal broker to turn to for help.Yet communities in many clientelistic settings are marked by multiple brokers who compete for a following.Such competition makes client choices,and the preferences guiding such choices,pivotal in fueling broker support.We examine client preferences for a pervasive broker-slum leaders-in the context of urban India.To identify resident preferences for slum leaders. we conducted an ethnographically informed conjoint survey experiment with 2,199 residents across 110 slums in two Indian cities.Contra standard emphases on shared ethnicity,we find residents place heaviest weight on a broker's capability to make claims on the state.A survey of 629 slum leaders finds client- preferred traits distinguish brokers from residents.In highlighting processes of broker selection,and the client preferences that undergird them,we underscore the centrality of clients in shaping local brokerage environments. INTRODUCTION ers,who vie to expand their personal following-their source of rents,patronage,and political sway. avan's home is set deep within the serpentine A burgeoning literature in comparative politics es- alleyways of Ganpati,one of the largest slums tablishes the pervasiveness of political brokers like in the north Indian city of Jaipur.With exposed Pavan,who facilitate the exchange of electoral sup- brick walls,chipping paint,and a corrugated steel roof port for access to goods,services,and protection in held by stones,the shanty is almost indistinguishable clientelistic settings (Nichter 2008;Stokes et al.2013; from others in the settlement.What differentiates it is Camp 2015;Holland and Palmer-Rubin 2015;Szwar- the inscription on Pavan's front door.The sign displays cberg 2015;Larreguy,Marshall,and Querubin 2016). his name,his position as adyaksh(president),and a lo- While these studies advance our understanding of tus flower-the symbol of the Bharatiya Janata Party clientelism,they tend to view machine politics-and (BJP).Pavan is an informal slum leader.He helps res- the hierarchies of brokers who enable it-from a top- idents secure government IDs and demand public ser- vices from the state.In a handful of folders,Pavan keeps down,party-centered perspective.Consequently,they predominantly conceptualize poor voters as passive copies of petitions,official correspondence,and notes recipients of election-time handouts,targeted by in- from party meetings,detailing his efforts to improve termediaries operating in their neighborhoods.The the slum.He has built a large following through these agency of poor voters in selecting the local brokers activities and is expected to translate his support into they support and turn to for help has largely been votes for the BJP.Pavan,however,cannot rest on his overlooked. laurels.He must maintain his clients'approval or risk In this paper,we argue that clients play a meaning- losing them to one of Ganpati's many other slum lead- ful role in selecting the brokers that staff electoral ma- chines.The neglect of client agency in broker selection stems from a lack of recognition of the intense competi- Adam Michael Auerbach is an Assistant Professor,School of Inter- tion among brokers for client support in many parts of national Service,American University,4400 Massachusetts Avenue NW,Washington,DC 20016(aauerba@american.edu) the world.Such competition enables clients to choose Tarig Thachil is an Associate Professor,Department of Political which broker to seek help from and follow.Recognition Science,Vanderbilt University,230 Appleton Place,Nashville,TN of such choice compels analyzing the underlying pref- 37203 (tariq.thachil@vanderbilt.edu) erences that inform broker selection by clients,which This study was preregistered with Evidence in Governance and Politics (20150619AA)and received IRB approval from Ameri- have not been systematically theorized or tested. can University (15098)and Yale University (1504015671).The au- We provide a theoretical framework for analyzing thors thank Ameya Balsekar,Leticia Bode,Natalia Bueno,Aditya client preferences for brokers,distinguishing two con- Dasgupta,Agustina Giraudy,Anirudh Krishna,Gareth Nellis,Irfan cerns that jointly structure such support.The first is Nooruddin,David Ohls,Kelly Rader,Mark Schneider,Susan Stokes, efficacy oriented:How likely is a broker to be able Yuhki Tajima,Emmanuel Teitelbaum.Milan Vaishnav,Michael Walton,Rebecca Weitz-Shapiro,Ashutosh Varshney,Erik Wibbels. to successfully demand and secure public goods and Adam Ziegfeld,and seminar participants at American University: services from the state?We argue evaluations of ef- the Centre for Policy Research,Delhi;Duke University;George- ficacy hinge on client perceptions of a broker's capa- town University;Harvard University;MIT;the New School;the Uni bility in making claims,their bureaucratic connected- versity of Pennsylvania:the University of Wisconsin-Madison;and ness to local municipal officials,and their partisan con- Yale University.Ved Prakash Sharma and the MORSELsurvey team provided excellent research assistance.This research was funded by nectedness to the incumbent political party.The second American University,Vanderbilt University,and Yale University Replication files are available on the American Political Science Re. view Dataverse:https://doi.org/10.7910/DVN/RUQ2KP Interview with Pavan,January 29,2011.Unless noted otherwise,all Received:August 11,2016;revised:April 21,2017;accepted:May 15. settlement and individual names have been changed to protect the 2018.First published online:July 11,2018. confidentiality of our informants. 775
American Political Science Review (2018) 112, 4, 775–791 doi:10.1017/S000305541800028X © American Political Science Association 2018 How Clients Select Brokers: Competition and Choice in India’s Slums ADAM MICHAEL AUERBACH American University TARIQ THACHIL Vanderbilt University Conventional models of clientelism often assume poor voters have little or no choice over which local broker to turn to for help. Yet communities in many clientelistic settings are marked by multiple brokers who compete for a following. Such competition makes client choices, and the preferences guiding such choices, pivotal in fueling broker support. We examine client preferences for a pervasive broker—slum leaders—in the context of urban India. To identify resident preferences for slum leaders, we conducted an ethnographically informed conjoint survey experiment with 2,199 residents across 110 slums in two Indian cities. Contra standard emphases on shared ethnicity, we find residents place heaviest weight on a broker’s capability to make claims on the state. A survey of 629 slum leaders finds clientpreferred traits distinguish brokers from residents. In highlighting processes of broker selection, and the client preferences that undergird them, we underscore the centrality of clients in shaping local brokerage environments. INTRODUCTION Pavan’s home is set deep within the serpentine alleyways of Ganpati, one of the largest slums in the north Indian city of Jaipur. With exposed brick walls, chipping paint, and a corrugated steel roof held by stones, the shanty is almost indistinguishable from others in the settlement. What differentiates it is the inscription on Pavan’s front door. The sign displays his name, his position as adyaksh (president), and a lotus flower—the symbol of the Bharatiya Janata Party (BJP). Pavan is an informal slum leader. He helps residents secure government IDs and demand public services from the state. In a handful of folders,Pavan keeps copies of petitions, official correspondence, and notes from party meetings, detailing his efforts to improve the slum. He has built a large following through these activities and is expected to translate his support into votes for the BJP. Pavan, however, cannot rest on his laurels. He must maintain his clients’ approval or risk losing them to one of Ganpati’s many other slum leadAdam Michael Auerbach is an Assistant Professor, School of International Service, American University, 4400 Massachusetts Avenue NW, Washington, DC 20016 (aauerba@american.edu) Tariq Thachil is an Associate Professor, Department of Political Science, Vanderbilt University, 230 Appleton Place, Nashville, TN 37203 (tariq.thachil@vanderbilt.edu) This study was preregistered with Evidence in Governance and Politics (20150619AA) and received IRB approval from American University (15098) and Yale University (1504015671). The authors thank Ameya Balsekar, Leticia Bode, Natalia Bueno, Aditya Dasgupta, Agustina Giraudy, Anirudh Krishna, Gareth Nellis, Irfan Nooruddin, David Ohls, Kelly Rader, Mark Schneider, Susan Stokes, Yuhki Tajima, Emmanuel Teitelbaum, Milan Vaishnav, Michael Walton, Rebecca Weitz-Shapiro, Ashutosh Varshney, Erik Wibbels, Adam Ziegfeld, and seminar participants at American University; the Centre for Policy Research, Delhi; Duke University; Georgetown University; Harvard University;MIT; the New School; the University of Pennsylvania; the University of Wisconsin-Madison; and Yale University.Ved Prakash Sharma and the MORSEL survey team provided excellent research assistance. This research was funded by American University, Vanderbilt University, and Yale University. Replication files are available on the American Political Science Review Dataverse: https://doi.org/10.7910/DVN/RUQ2KP. Received: August 11, 2016; revised: April 21, 2017; accepted: May 15, 2018. First published online: July 11, 2018. ers, who vie to expand their personal following—their source of rents, patronage, and political sway.1 A burgeoning literature in comparative politics establishes the pervasiveness of political brokers like Pavan, who facilitate the exchange of electoral support for access to goods, services, and protection in clientelistic settings (Nichter 2008; Stokes et al. 2013; Camp 2015; Holland and Palmer-Rubin 2015; Szwarcberg 2015; Larreguy, Marshall, and Querubin 2016). While these studies advance our understanding of clientelism, they tend to view machine politics—and the hierarchies of brokers who enable it—from a topdown, party-centered perspective. Consequently, they predominantly conceptualize poor voters as passive recipients of election-time handouts, targeted by intermediaries operating in their neighborhoods. The agency of poor voters in selecting the local brokers they support and turn to for help has largely been overlooked. In this paper, we argue that clients play a meaningful role in selecting the brokers that staff electoral machines. The neglect of client agency in broker selection stems from a lack of recognition of the intense competition among brokers for client support in many parts of the world. Such competition enables clients to choose which broker to seek help from and follow.Recognition of such choice compels analyzing the underlying preferences that inform broker selection by clients, which have not been systematically theorized or tested. We provide a theoretical framework for analyzing client preferences for brokers, distinguishing two concerns that jointly structure such support. The first is efficacy oriented: How likely is a broker to be able to successfully demand and secure public goods and services from the state? We argue evaluations of efficacy hinge on client perceptions of a broker’s capability in making claims, their bureaucratic connectedness to local municipal officials, and their partisan connectedness to the incumbent political party.The second 1 Interview with Pavan, January 29, 2011. Unless noted otherwise, all settlement and individual names have been changed to protect the confidentiality of our informants. 775 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
Adam Michael Auerbach and Tarig Thachil concern is distributive:how likely is a broker to chan- theoretical framework for understanding those pref- nel secured benefits to a client's household?We fo- erences centered on the distributive and efficacy con- cus on shared partisan or ethnic identities between the cerns of clients. broker and client as determinants of these distributive Our results,interpreted through this distinction be- expectations. tween efficacy and distributive concerns,are also the- Empirically,we examine client preferences for bro- oretically significant.First,our findings challenge con- kers through a study of a substantively important ventional wisdom on Asian and African politics that class of intermediaries:informal slum leaders.Poor anticipates distributive expectations based on coeth- urban neighborhoods are iconic settings for theories nicity will overwhelmingly shape political preferences of clientelism,making them especially important are- (Chandra 2004:Posner 2005).While clients do prefer nas to examine (Stokes 1995,Auyero 2000).Slums coethnics,we find they value certain nonethnic indica- are estimated to house approximately 850 million peo- tors of a slum leader's efficacy,particularly their educa- ple worldwide,making their leaders central figures in tion,even more highly.We also find,contra some prior the distributive politics of developing cities.?For res- studies,that the benefits for good performance do not idents,slum leaders are focal points for fighting evic- exclusively accrue to coethnics(Adida et al.2017;Carl- tion and demanding development.For politicians,they son 2015).Indeed,we find capability and connectivity are uniquely positioned to influence residents,encour- can even compensate for a lack of coethnicity.This lat- age turnout,and organize rallies.Through a combined ter finding is especially important,given that our bro- three years of qualitative fieldwork in Indian slums,we ker survey reveals the supply of coethnic brokers in di- found settlement leadership to be contested,multifo- verse slum settlements is more constrained than that of cal,and rapidly constructed to push back against evic- capable brokers. tion and claim public services.In such competitive bro- Second.our findings on education suggest varia- 上二 kerage environments,Indian slum residents wield sig- tion in broker efficacy for their clients should receive nificant agency and choice in selecting whom they ap- greater attention in models of clientelism.Extant stud- proach for problem-solving. ies have focused on conceptualizing broker efficacy To assess the relative salience of efficacy and dis- from the perspective of parties(Camp 2015;Larreguy, tributive concerns in shaping slum resident prefer- Marshall,and Querubin 2016).Variation in client- ences for brokers,we conducted an ethnographically facing efficacy is further obscured by a preoccupation informed conjoint survey experiment with 2,199 indi- with top-down,episodic forms of distributive politics viduals across 110 slums in two north Indian cities such as vote buying.Such activities mute the impor- Survey respondents were asked to choose between tance of individual skills in advancing client claims,a two hypothetical candidates running for the informal primary role brokers play between elections.Our find- position of slum president (adyaksh).We use ethno- ings support recent calls for paying greater attention to graphic insights to operationalize contextual indicators such everyday lobbying roles,and not simply a brokers' of each candidate's ethnicity and partisanship,their episodic roles as dispensers of election-time handouts claim-making capability,and their connectivity to both (Berenschot 2010:Nichter 2014:Bussell 2018:Kruks- local bureaucrats and the incumbent party.A paral- Wisner 2018). lel experiment asked respondents to choose between Empirically,our study provides the first systematic S5.501g two hypothetical residents as potential neighbors,al- analysis,to our knowledge,of client preferences for lowing us to distinguish political preferences for lead- brokers.We hope to spark a research agenda on the ers from social preferences for neighbors.Finally,we determinants of client preferences for informal lead- subject our experimental findings to further scrutiny ers across varied national and local contexts.We also using data from a survey of 629 slum leaders,whom seek to contribute to our empirical understanding of we surveyed across our 110 settlements.Specifically,we distributive politics within urban slums and migrant assess whether client-preferred traits distinguish actual communities,an understudied electorate that is prolif- slum leaders from ordinary residents erating across much of the developing world(Thachil This paper advances the study of distributive,eth- 2017).3 In this arena,we present evidence from the first nic,and urban politics.Theoretically,we draw atten- large and representative survey of slum leaders ever tion to the neglected phenomenon of broker selection conducted by clients.We build on important work showing that clients often have nontrivial agency (Auyero 2000) ranging from initiating requests for services (Nichter CLIENT PREFERENCES MATTER and Peress 2017)to defecting from nonresponsive ma- Conventional models of clientelism afford little agency chines (Taylor-Robinson 2010).We extend this schol- to poor voters in selecting the brokers they seek help arship by arguing clients can also shape who staffs from and follow.Influential studies assume the pres- the local machine,especially in competitive brokerage ence of brokers without probing the nature of their conditions.When clients can exercise choice in broker support(Stokes 2005;Nichter 2008),or analyze how selection,we argue it is important to analyze their pref- parties select brokers to include within their orga- erences for specific broker attributes.We provide a nizational networks (Camp 2015;Szwarcberg 2015; United Nations (2015,2).Officially,65 million people in India re- See Post(2018)for a larger discussion on urban politics in the de- side in urban slums(2011 Census of India). veloping world. 776
Adam Michael Auerbach and Tariq Thachil concern is distributive: how likely is a broker to channel secured benefits to a client’s household? We focus on shared partisan or ethnic identities between the broker and client as determinants of these distributive expectations. Empirically, we examine client preferences for brokers through a study of a substantively important class of intermediaries: informal slum leaders. Poor urban neighborhoods are iconic settings for theories of clientelism, making them especially important arenas to examine (Stokes 1995, Auyero 2000). Slums are estimated to house approximately 850 million people worldwide, making their leaders central figures in the distributive politics of developing cities.2 For residents, slum leaders are focal points for fighting eviction and demanding development. For politicians, they are uniquely positioned to influence residents, encourage turnout, and organize rallies. Through a combined three years of qualitative fieldwork in Indian slums, we found settlement leadership to be contested, multifocal, and rapidly constructed to push back against eviction and claim public services. In such competitive brokerage environments, Indian slum residents wield significant agency and choice in selecting whom they approach for problem-solving. To assess the relative salience of efficacy and distributive concerns in shaping slum resident preferences for brokers, we conducted an ethnographically informed conjoint survey experiment with 2,199 individuals across 110 slums in two north Indian cities. Survey respondents were asked to choose between two hypothetical candidates running for the informal position of slum president (adyaksh). We use ethnographic insights to operationalize contextual indicators of each candidate’s ethnicity and partisanship, their claim-making capability, and their connectivity to both local bureaucrats and the incumbent party. A parallel experiment asked respondents to choose between two hypothetical residents as potential neighbors, allowing us to distinguish political preferences for leaders from social preferences for neighbors. Finally, we subject our experimental findings to further scrutiny using data from a survey of 629 slum leaders, whom we surveyed across our 110 settlements. Specifically, we assess whether client-preferred traits distinguish actual slum leaders from ordinary residents. This paper advances the study of distributive, ethnic, and urban politics. Theoretically, we draw attention to the neglected phenomenon of broker selection by clients. We build on important work showing that clients often have nontrivial agency (Auyero 2000), ranging from initiating requests for services (Nichter and Peress 2017) to defecting from nonresponsive machines (Taylor-Robinson 2010). We extend this scholarship by arguing clients can also shape who staffs the local machine, especially in competitive brokerage conditions. When clients can exercise choice in broker selection, we argue it is important to analyze their preferences for specific broker attributes. We provide a 2 United Nations (2015, 2). Officially, 65 million people in India reside in urban slums (2011 Census of India). theoretical framework for understanding those preferences centered on the distributive and efficacy concerns of clients. Our results, interpreted through this distinction between efficacy and distributive concerns, are also theoretically significant. First, our findings challenge conventional wisdom on Asian and African politics that anticipates distributive expectations based on coethnicity will overwhelmingly shape political preferences (Chandra 2004; Posner 2005). While clients do prefer coethnics, we find they value certain nonethnic indicators of a slum leader’s efficacy, particularly their education, even more highly. We also find, contra some prior studies, that the benefits for good performance do not exclusively accrue to coethnics (Adida et al. 2017; Carlson 2015). Indeed, we find capability and connectivity can even compensate for a lack of coethnicity. This latter finding is especially important, given that our broker survey reveals the supply of coethnic brokers in diverse slum settlements is more constrained than that of capable brokers. Second, our findings on education suggest variation in broker efficacy for their clients should receive greater attention in models of clientelism. Extant studies have focused on conceptualizing broker efficacy from the perspective of parties (Camp 2015; Larreguy, Marshall, and Querubin 2016). Variation in clientfacing efficacy is further obscured by a preoccupation with top-down, episodic forms of distributive politics such as vote buying. Such activities mute the importance of individual skills in advancing client claims, a primary role brokers play between elections. Our findings support recent calls for paying greater attention to such everyday lobbying roles, and not simply a brokers’ episodic roles as dispensers of election-time handouts (Berenschot 2010; Nichter 2014; Bussell 2018; KruksWisner 2018). Empirically, our study provides the first systematic analysis, to our knowledge, of client preferences for brokers. We hope to spark a research agenda on the determinants of client preferences for informal leaders across varied national and local contexts. We also seek to contribute to our empirical understanding of distributive politics within urban slums and migrant communities, an understudied electorate that is proliferating across much of the developing world (Thachil 2017).3 In this arena, we present evidence from the first large and representative survey of slum leaders ever conducted. CLIENT PREFERENCES MATTER Conventional models of clientelism afford little agency to poor voters in selecting the brokers they seek help from and follow. Influential studies assume the presence of brokers without probing the nature of their support (Stokes 2005; Nichter 2008), or analyze how parties select brokers to include within their organizational networks (Camp 2015; Szwarcberg 2015; 3 See Post (2018) for a larger discussion on urban politics in the developing world. 776 Downloaded from https://www.cambridge.org/core. 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How Clients Select Brokers Larreguy,Marshall,and Querubin 2016).In sharp In neglecting this reality of client choice in select- contrast,there have been no efforts to systemati- ing brokers,party-centric studies have overlooked the cally theorize and examine client preferences for bro- client preferences empowered by such choice.At most, kers.Auyero's(2000,153)assertion,made nearly two these studies anticipate clients will prefer a broker decades ago,that studies of clientelism rarely take the with connections to party organizations.Such connec- agency of clients seriously still rings true today. tions unlock the top-down flow of party handouts dur This neglect of client preferences stems from in- ing elections that are seen to motivate resident sup- sufficient recognition of competition among brokers port.Client approval of a broker should therefore for clients,which enables a degree of choice in who hinge upon a party's prior approval,especially from clients can turn to for help(Scott 1977).Many influen- the resource-rich incumbent at the center of most top- tial studies of clientelism model interactions between down models. voters and a single dominant machine (Stokes 2005; By contrast,in competitive brokerage environments, Nichter 2008:Stokes et al.2013:Gans-Morse.Maz- client approval does not simply flow axiomatically from zuca,and Nichter 2014).In such settings,client choice prior party approval.Slum leaders,for example,must can only occur via intra-party competition among bro- attract a following through entrepreneurial sweat,by kers,which is rarely examined.Other frameworks advancing everyday resident demands through local specify a single broker (Gingerich and Medina 2013: lobbying and competing with others in the settlement Rueda 2015)or multiple brokers who each hold spa- who seek to engage in netagiri,or politicking.Indeed. tially distinct monopolies over clients (Gans-Morse, party leaders frequently consider a slum leader's local Mazzuca,and Nichter 2014;Camp 2015).Across all of popularity with clients in their own organizational deci- these models,clients are bereft of options,rendering sions.Party leaders in our study cities noted they could their preferences-and efforts to investigate them- not manufacture client support for any individual sim- redundant. ply by granting them a position within their local or- However,assumptions of single-party or single ganization.Instead they noted the need for brokers to 4号元 broker dominance do not align with the political re- be from the slum itself,and the importance of resident alities of many countries and communities.An ex- approval in shaping their own evaluations: pert survey (Kitschelt 2011)documents competitive "bilateral or multilateral"clientelistic party systems Party Elite 1:See,there would always be some leadership as more common than "unilateral clientelism.4 Fur- in the bastis;some people who were active and working ther,even within "unilateral machines,"ethnographic for people.Our party needed someone like this in the set- studies find evidence of microlevel competition among tlement.It was through such people that we strengthened brokers (Auyero 2000;Zarazaga 2014).In our study our position in the bastis...These are the people we would setting,we found slum dwellers reside in highly com- select for a party position. petitive brokerage environments.Our survey respon- 是 dents provided nearly 1,000 slum leader names,or Party Elite 2:Someone from the community emerges as a roughly 9 per settlement,and most slums had leaders strong leader,has a public following,and has strong influ- with formal affiliations to each of the city's major po- ence.In that case,we must approach him and offer him a litical parties. position. Competition grants clients a degree of choice in Author:You mean when there is someone the local peo- choosing whom they seek assistance from.In inter- ple already support,you then approach him and bring him views,Indian slum residents repeatedly noted they ac- into the party? tively selected their leaders: Party Elite 2:Yes,somehow we have to make him part of the party. Resident 1:Slum leaders help us because the residents of the basti [slum have chosen them as their leader. Party Elite 3:We [the party]can't make someone a neta [leader]just by giving him neta clothes and making him stand on the road.In that case he would just be a statue. Resident 2:We chose them so that they can help us when They must first have the support of residents to be a there is a problem. leader.10 Evidence from our survey of 629 slum leaders(de- Resident 3:Leaders help poor people who have no one in the government to go to...We have chosen them for a tailed below)provides further corroboration of the im- reason. portance of client support in solidifying a broker's ap- peal to political parties.We asked slum leaders what the biggest reason was for securing a position (pad) within a party.56.8%said popularity within the slum 4"Clientelistic effort proceeds within a bilateral or multilateral competitive framework"in contexts across Europe (Italy,Austria. the next most frequent item accounted for 10.11%of L Bulgaria,Ukraine),Asia (Indonesia,India,and Taiwan),Africa (Ghana and Nigeria),and even Latin America (Brazil and Colom- bia)(Kitschelt 2011,9) Interview with Congress ex-MLA,Bhopal,January 25,2017 Interview with Kamal Nagar Resident 7 August 2017 Interview with BJP municipal councilor,Jaipur,February 13,2017 6 Interview with Naya Colony Resident 3,August 2017 10 Interview with Congress municipal councilor,Bhopal,January 23. Interview with Kamal Nagar Resident 9,August 2017 2017 777
How Clients Select Brokers Larreguy, Marshall, and Querubin 2016). In sharp contrast, there have been no efforts to systematically theorize and examine client preferences for brokers. Auyero’s (2000, 153) assertion, made nearly two decades ago, that studies of clientelism rarely take the agency of clients seriously still rings true today. This neglect of client preferences stems from insufficient recognition of competition among brokers for clients, which enables a degree of choice in who clients can turn to for help (Scott 1977). Many influential studies of clientelism model interactions between voters and a single dominant machine (Stokes 2005; Nichter 2008; Stokes et al. 2013; Gans-Morse, Mazzuca, and Nichter 2014). In such settings, client choice can only occur via intra-party competition among brokers, which is rarely examined. Other frameworks specify a single broker (Gingerich and Medina 2013; Rueda 2015) or multiple brokers who each hold spatially distinct monopolies over clients (Gans-Morse, Mazzuca, and Nichter 2014; Camp 2015). Across all of these models, clients are bereft of options, rendering their preferences—and efforts to investigate them— redundant. However, assumptions of single-party or singlebroker dominance do not align with the political realities of many countries and communities. An expert survey (Kitschelt 2011) documents competitive “bilateral or multilateral” clientelistic party systems as more common than “unilateral clientelism.”4 Further, even within “unilateral machines,” ethnographic studies find evidence of microlevel competition among brokers (Auyero 2000; Zarazaga 2014). In our study setting, we found slum dwellers reside in highly competitive brokerage environments. Our survey respondents provided nearly 1,000 slum leader names, or roughly 9 per settlement, and most slums had leaders with formal affiliations to each of the city’s major political parties. Competition grants clients a degree of choice in choosing whom they seek assistance from. In interviews, Indian slum residents repeatedly noted they actively selected their leaders: Resident 1: Slum leaders help us because the residents of the basti [slum] have chosen them as their leader.5 * Resident 2: We chose them so that they can help us when there is a problem.6 * Resident 3: Leaders help poor people who have no one in the government to go to…We have chosen them for a reason.7 4 “Clientelistic effort proceeds within a bilateral or multilateral competitive framework” in contexts across Europe (Italy, Austria, Bulgaria, Ukraine), Asia (Indonesia, India, and Taiwan), Africa (Ghana and Nigeria), and even Latin America (Brazil and Colombia) (Kitschelt 2011, 9). 5 Interview with Kamal Nagar Resident 7, August 2017. 6 Interview with Naya Colony Resident 3, August 2017. 7 Interview with Kamal Nagar Resident 9, August 2017. In neglecting this reality of client choice in selecting brokers, party-centric studies have overlooked the client preferences empowered by such choice. At most, these studies anticipate clients will prefer a broker with connections to party organizations. Such connections unlock the top-down flow of party handouts during elections that are seen to motivate resident support. Client approval of a broker should therefore hinge upon a party’s prior approval, especially from the resource-rich incumbent at the center of most topdown models. By contrast, in competitive brokerage environments, client approval does not simply flow axiomatically from prior party approval. Slum leaders, for example, must attract a following through entrepreneurial sweat, by advancing everyday resident demands through local lobbying and competing with others in the settlement who seek to engage in netagiri, or politicking. Indeed, party leaders frequently consider a slum leader’s local popularity with clients in their own organizational decisions. Party leaders in our study cities noted they could not manufacture client support for any individual simply by granting them a position within their local organization. Instead they noted the need for brokers to be from the slum itself, and the importance of resident approval in shaping their own evaluations: Party Elite 1: See, there would always be some leadership in the bastis; some people who were active and working for people. Our party needed someone like this in the settlement. It was through such people that we strengthened our position in the bastis...These are the people we would select for a party position.8 * Party Elite 2: Someone from the community emerges as a strong leader, has a public following, and has strong influence. In that case, we must approach him and offer him a position. Author: You mean when there is someone the local people already support, you then approach him and bring him into the party? Party Elite 2: Yes, somehow we have to make him part of the party.9 * Party Elite 3: We [the party] can’t make someone a neta [leader] just by giving him neta clothes and making him stand on the road. In that case he would just be a statue. They must first have the support of residents to be a leader.10 Evidence from our survey of 629 slum leaders (detailed below) provides further corroboration of the importance of client support in solidifying a broker’s appeal to political parties. We asked slum leaders what the biggest reason was for securing a position (pad) within a party. 56.8% said popularity within the slum (the next most frequent item accounted for 10.11% of 8 Interview with Congress ex-MLA, Bhopal, January 25, 2017. 9 Interview with BJP municipal councilor, Jaipur, February 13, 2017. 10 Interview with Congress municipal councilor, Bhopal, January 23, 2017. 777 Downloaded from https://www.cambridge.org/core. 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Adam Michael Auerbach and Tarig Thachil responses).Only 9.56%said top-down,preexisting ties ties hold in their top-down evaluations of brokers.The to party leaders. first is a distribution-based concern:How likely am I These observations also align with an earlier wave (the client)to be included within a broker's distribu- of scholarship on urban politics in Latin America. tive network?The second is an efficacy-based concern: which described slums as competitive brokerage en- How likely is this broker to acquire material benefits vironments in which leaders were local residents to distribute?While these concerns can be complemen- who had to work to gain client approval(Ray 1969; tary,each highlights distinct attributes clients will value Cornelius 1975:Gay 1994).These studies,however. in their local broker stop short of theorizing and testing the implications of competitive brokerage for processes of client selec- tion and the nature of client preferences.Our argument Distributive Concerns also aligns with recent studies underscoring that clients Studies of how parties evaluate brokers have empha- have nontrivial agency,ranging from initiating requests sized the importance of a broker's efficiency in convert- for services(Nichter and Peress 2017)to defecting from ing party resources into votes (Stokes et al.2013;Lar- machines that do not reward them (Taylor-Robinson reguy,Marshall,and Querubin 2016).Given it is neither 2010)and other mechanisms of constrained account- feasible nor efficient for parties to provide benefits to ability (Hilgers 2012).However,these studies have fo- all voters,brokers can help ensure benefits reach those cused on how such agency affects the downward re- the party wishes to cultivate as clients.Accordingly,par- sponsiveness of party machines toward clients.None ties are said to prefer brokers with pre-poll information have theoretically linked competition between brokers about client partisan preferences(Nichter 2008;Stokes with client agency in selecting local leaders,or empir- et al.2013),post-poll information about electoral com- ically examined the preferences guiding such bottom- pliance(Stokes 2005),and probity in passing on party up selection decisions. resources to voters (Rueda 2015;Larreguy,Marshall, In sum,brokers in competitive environments must and Querubin 2016). often vie for the client support that underpins their lo- Switching to a client's perspective,excludable target- cal authority.In generating choice,competition affords ing raises a distributive concern:which broker's net- clients an opportunity to select brokers they most pre- work am I most likely to be included within?Under fer,rather than accept a broker anointed by political competitive conditions,such expectations can shape elites.How,then,is client choice exercised? the preferences clients draw on to choose which bro- We found two primary alternatives within our study ker to support.What indicators might clients draw on setting.The first are discrete moments of selection. in formulating these distributive expectations? principally informal elections and community meet- Past literature suggests commitment problems in ings.Seventy-seven percent of the 1,925 respondents to quid pro quo protocols are ameliorated when bro- a 2012 author survey of slum residents across our two kers and voters are embedded within the same so- study cities(Auerbach 2016)acknowledged informal cial or organizational network.Consequently,schol- leadership in their settlement.Over half of this sub- ars anticipate shared partisan affiliations as central to set reported selecting their leaders through informal structuring clientelist transactions.Risk-averse parties elections or community meetings.This figure matches (Cox and McCubbins 1986)and brokers(Dunning and S5.501g our slum leader survey,where 38%of respondents Nilekani 2013;Stokes et al.2013)are argued to fa- claimed they were selected through informal elections vor copartisan clients most likely to reciprocate at or community meetings.Research on slums in India the polls.From the client's perspective,citizens who and Latin America has described similar selection pro- share partisan affiliations with their broker will there- cesses (Ray 1969;Gay 1994;Burgwal 1995;Jha,Rao, fore hold higher expectations of getting benefits than and Woolcock 2007).The second pathway of broker those who do not (Calvo and Murillo 2013).Thus,we selection is through iterative,everyday choices made expect residents to prefer slum leaders of the same par- by clients in whom to seek help from.These individ- tisan affiliation.11 ual choices aggregate into a distribution of support for Studies of clientelism in South Asia and Africa sim- slum leaders. ilarly emphasize the utility of shared ethnic networks. Irrespective of whether brokers are selected through The stickiness and visibility of ethnic markers be- informal elections,community meetings,or decentral- stow an informational advantage over nonethnic cat- ized day-to-day resident decisions,their success in com egories such as class.Such advantages are argued to petitive settings hinges on client preferences.We now solve commitment problems within clientelist pacts turn to providing a theoretical framework for analyzing (Chandra 2004:Posner 2005:Carlson 2015).Addition- such preferences. ally.coethnics are often embedded within dense so- cial networks,enabling them to build trust(Fershtman and Gneezy 2001).These and related arguments have WHICH BROKERS WILL THE URBAN POOR primarily been made with regard to shared ethnicity PREFER? between voters and political candidates (Chauchard 2016).However,their logic suggests slum residents will We pinpoint two key concerns that shape client pref- erences for brokers.Each provides a client-centered corollary to previously articulated concerns that par- 11 86.49%of our 629 surveyed slum leaders had partisan affiliations. 778
Adam Michael Auerbach and Tariq Thachil responses). Only 9.56% said top-down, preexisting ties to party leaders. These observations also align with an earlier wave of scholarship on urban politics in Latin America, which described slums as competitive brokerage environments in which leaders were local residents who had to work to gain client approval (Ray 1969; Cornelius 1975; Gay 1994). These studies, however, stop short of theorizing and testing the implications of competitive brokerage for processes of client selection and the nature of client preferences.Our argument also aligns with recent studies underscoring that clients have nontrivial agency, ranging from initiating requests for services (Nichter and Peress 2017) to defecting from machines that do not reward them (Taylor-Robinson 2010) and other mechanisms of constrained accountability (Hilgers 2012). However, these studies have focused on how such agency affects the downward responsiveness of party machines toward clients. None have theoretically linked competition between brokers with client agency in selecting local leaders, or empirically examined the preferences guiding such bottomup selection decisions. In sum, brokers in competitive environments must often vie for the client support that underpins their local authority. In generating choice, competition affords clients an opportunity to select brokers they most prefer, rather than accept a broker anointed by political elites. How, then, is client choice exercised? We found two primary alternatives within our study setting. The first are discrete moments of selection, principally informal elections and community meetings. Seventy-seven percent of the 1,925 respondents to a 2012 author survey of slum residents across our two study cities (Auerbach 2016) acknowledged informal leadership in their settlement. Over half of this subset reported selecting their leaders through informal elections or community meetings. This figure matches our slum leader survey, where 38% of respondents claimed they were selected through informal elections or community meetings. Research on slums in India and Latin America has described similar selection processes (Ray 1969; Gay 1994; Burgwal 1995; Jha, Rao, and Woolcock 2007). The second pathway of broker selection is through iterative, everyday choices made by clients in whom to seek help from. These individual choices aggregate into a distribution of support for slum leaders. Irrespective of whether brokers are selected through informal elections, community meetings, or decentralized day-to-day resident decisions, their success in competitive settings hinges on client preferences. We now turn to providing a theoretical framework for analyzing such preferences. WHICH BROKERS WILL THE URBAN POOR PREFER? We pinpoint two key concerns that shape client preferences for brokers. Each provides a client-centered corollary to previously articulated concerns that parties hold in their top-down evaluations of brokers. The first is a distribution-based concern: How likely am I (the client) to be included within a broker’s distributive network? The second is an efficacy-based concern: How likely is this broker to acquire material benefits to distribute? While these concerns can be complementary, each highlights distinct attributes clients will value in their local broker. Distributive Concerns Studies of how parties evaluate brokers have emphasized the importance of a broker’s efficiency in converting party resources into votes (Stokes et al. 2013; Larreguy,Marshall, and Querubin 2016).Given it is neither feasible nor efficient for parties to provide benefits to all voters, brokers can help ensure benefits reach those the party wishes to cultivate as clients.Accordingly, parties are said to prefer brokers with pre-poll information about client partisan preferences (Nichter 2008; Stokes et al. 2013), post-poll information about electoral compliance (Stokes 2005), and probity in passing on party resources to voters (Rueda 2015; Larreguy, Marshall, and Querubin 2016). Switching to a client’s perspective, excludable targeting raises a distributive concern: which broker’s network am I most likely to be included within? Under competitive conditions, such expectations can shape the preferences clients draw on to choose which broker to support. What indicators might clients draw on in formulating these distributive expectations? Past literature suggests commitment problems in quid pro quo protocols are ameliorated when brokers and voters are embedded within the same social or organizational network. Consequently, scholars anticipate shared partisan affiliations as central to structuring clientelist transactions. Risk-averse parties (Cox and McCubbins 1986) and brokers (Dunning and Nilekani 2013; Stokes et al. 2013) are argued to favor copartisan clients most likely to reciprocate at the polls. From the client’s perspective, citizens who share partisan affiliations with their broker will therefore hold higher expectations of getting benefits than those who do not (Calvo and Murillo 2013). Thus, we expect residents to prefer slum leaders of the same partisan affiliation.11 Studies of clientelism in South Asia and Africa similarly emphasize the utility of shared ethnic networks. The stickiness and visibility of ethnic markers bestow an informational advantage over nonethnic categories such as class. Such advantages are argued to solve commitment problems within clientelist pacts (Chandra 2004; Posner 2005; Carlson 2015). Additionally, coethnics are often embedded within dense social networks, enabling them to build trust (Fershtman and Gneezy 2001). These and related arguments have primarily been made with regard to shared ethnicity between voters and political candidates (Chauchard 2016). However, their logic suggests slum residents will 11 86.49% of our 629 surveyed slum leaders had partisan affiliations. 778 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
How Clients Select Brokers also prefer coethnic local leaders,whom they expect to to secure resources(Zarazaga 2014;Camp 2015;Szwar- favor them in the distribution of resources. cberg 2015).But even this recognition has not yielded insights into how clients assess broker efficacy and the degree to which such evaluations guide broker selec- Efficacy Concerns tion by clients Scholars theorizing how parties evaluate brokers also Instead,prior scholarship has primarily assumed discuss the importance of a broker's efficacy,typically clients can rely on a broker's past performance in de- conceived in terms of their ability to mobilize vot- termining their future efficacy (Stokes et al.2013). ers during elections and rallies(Szwarcberg 2015),and Established slum leaders can and do rely on prior suc- monitor their compliance at the ballot box (Stokes cesses to recruit supporters.However,if clients exclu- et al.2013).This focus on a broker's electoral efficacy sively privilege past accomplishments,aspiring brokers is enabled by a preoccupation with vote buying,a top- with no record stand little chance of poaching sup- down strategy in which parties deliver handouts to bro- port from even minimally competent existing leaders. kers.and brokers distribute them to clients This model predicts a convergence to a low-turnover This"handout model"of clientelism paints brokers brokerage environment.We observe the opposite in as election-time distributive nodes with little individ our field sites,where new leaders constantly surface ual lobbying power (Gonzalez-Ocantos et al.2012; to compete against-and often displace-existing lead- Larreguy,Marshall,and Querubin 2016).The bene- ers.Our survey of slum leaders found evidence of new fits involved-petty cash,sacks of grain,liquor-are cohorts of leaders and consistent competition among modest.Further,their allocation is often managed by leaders.13 campaign operatives,who distribute them to brokers This data aligns with the phenomenon of a bulging as either a fixed allotment or variable handouts deter- class of ambitious yet unemployed Indian youth who mined by client demographics(Gans-Morse,Mazzuca, often turn to politics to generate income and connec- and Nichter 2014).A broker's individual skill thus plays tions (Jeffrey 2010).These rising leaders can break into 4号元 little role in determining the benefits they have to dis the current structure of leadership if they can signal the tribute.Recent models of vote-buying even explicitly potential to get things done better than current alterna- assume all brokers to be equally capable,and explain tives.Take Hari Singh,who rose to power by snatching variation in their efficacy (again conceptualized from supporters from a preexisting slum leader: the party's perspective)as dependent on the extent to which party superiors can monitor and punish them [There is]one leader who people stopped following after I (Larreguy,Marshall,and Querubin 2016,165). came to the slum because I knew more than him...I know A client-centered perspective widens the aperture of everything about the system,whether you go to the Mu- observation to broker activities between the votes.This nicipal Corporation,Electricity Board,Development Au- focus reveals the importance of their individual capa- thority,or Collectorate.I know how to solve problems re- 是 lated to these departments.Hence,that leader became less bilities in everyday acts of problem-solving in response popular.14 to resident demands.These demands reverse the flow of activity upward,revealing the importance of a bro- The fluid and competitive nature of slum leadership ker's efficacy in bringing requests to the notice of polit- thus affords residents ongoing choices in which slum ical elites.Such skill is central to securing resources for leader they view as most efficacious.15 clients,and thereby popularity among them.Popularity What characteristics do residents use to form com- is the basis upon which brokers attract party patronage, parisons of the relative efficacy of the array of promotions within party organizations,and day-to-day leaders-both established and aspiring-who jostle for rents from residents seeking help(Auerbach 2016).12 power in their localities?We argue that clients eval- We are hardly the first to acknowledge the signifi- uate efficacy potential via attributes that indicate a cance of routine problem-solving in the repertoire of broker's connectivity to actors controlling government broker activities (Auyero 2000;Krishna 2002),as well benefits,and capability for effectively making claims. as the importance of broker efficacy in generating a fol- lowing(Ray 1969;Cornelius 1975).Yet most prior stud- ies simply describe such activities as essential,without 13 Respondents had varying tenure lengths as slum leaders,attest- theorizing the implications of variable client-facing ef- ing to the openness of the brokerage environment.The mean tenure length was 20 years,with a standard deviation of just over 10 years. ficacy.More recent studies of Argentine brokers note We asked respondents how many slum leaders were in operation 四 that broker popularity is a function of variable abilities when they began slum leadership.Responses indicated a stably com- petitive environment,with an average of 10.18 competitors for lead- ers who began more than 25 years ago,and 9.5 competitors for those 12 In terms of election-time rents,one slum leader told us that influ- o began within the past five ye Interview with Hari Singh.June 7 2016. ential brokers in his settlement received roughly Rs.20,000($300) 15 This assertion also holds for those settlements that emerge from parties in a recent municipal election-four months of income through large-scale,preplanned land invasions in which informa for many of their neighbors(interview with Gurjar,Jaipur,June leadership is initially present-a type of settlement formation most 28,2011).Another benefit,promotions within party organizations, frequently documented in Latin America (Collier 1976;Gilbert comes with increased access to patronage and government contacts 1998).Scholars describe these settlements as competitive brokerage 士 Our surveyed slum leaders did receive such promotions:278 of 629 environments,where new challengers emerge to compete with estab- of them had held multiple formal party positions,which tended to lished slum leaders,affording residents ongoing choice over leader follow an upward trajectory. selection (Ray 1969:Gay 1994;Burgwal 1995). 779
How Clients Select Brokers also prefer coethnic local leaders, whom they expect to favor them in the distribution of resources. Efficacy Concerns Scholars theorizing how parties evaluate brokers also discuss the importance of a broker’s efficacy, typically conceived in terms of their ability to mobilize voters during elections and rallies (Szwarcberg 2015), and monitor their compliance at the ballot box (Stokes et al. 2013). This focus on a broker’s electoral efficacy is enabled by a preoccupation with vote buying, a topdown strategy in which parties deliver handouts to brokers, and brokers distribute them to clients. This “handout model” of clientelism paints brokers as election-time distributive nodes with little individual lobbying power (Gonzalez-Ocantos et al. 2012; Larreguy, Marshall, and Querubin 2016). The benefits involved—petty cash, sacks of grain, liquor—are modest. Further, their allocation is often managed by campaign operatives, who distribute them to brokers as either a fixed allotment or variable handouts determined by client demographics (Gans-Morse, Mazzuca, and Nichter 2014).A broker’s individual skill thus plays little role in determining the benefits they have to distribute. Recent models of vote-buying even explicitly assume all brokers to be equally capable, and explain variation in their efficacy (again conceptualized from the party’s perspective) as dependent on the extent to which party superiors can monitor and punish them (Larreguy, Marshall, and Querubin 2016, 165). A client-centered perspective widens the aperture of observation to broker activities between the votes. This focus reveals the importance of their individual capabilities in everyday acts of problem-solving in response to resident demands. These demands reverse the flow of activity upward, revealing the importance of a broker’s efficacy in bringing requests to the notice of political elites. Such skill is central to securing resources for clients, and thereby popularity among them. Popularity is the basis upon which brokers attract party patronage, promotions within party organizations, and day-to-day rents from residents seeking help (Auerbach 2016).12 We are hardly the first to acknowledge the significance of routine problem-solving in the repertoire of broker activities (Auyero 2000; Krishna 2002), as well as the importance of broker efficacy in generating a following (Ray 1969; Cornelius 1975).Yet most prior studies simply describe such activities as essential, without theorizing the implications of variable client-facing efficacy. More recent studies of Argentine brokers note that broker popularity is a function of variable abilities 12 In terms of election-time rents, one slum leader told us that influential brokers in his settlement received roughly Rs. 20,000 ($300) from parties in a recent municipal election—four months of income for many of their neighbors (interview with Gurjar, Jaipur, June 28, 2011). Another benefit, promotions within party organizations, comes with increased access to patronage and government contacts. Our surveyed slum leaders did receive such promotions: 278 of 629 of them had held multiple formal party positions, which tended to follow an upward trajectory. to secure resources (Zarazaga 2014; Camp 2015; Szwarcberg 2015). But even this recognition has not yielded insights into how clients assess broker efficacy and the degree to which such evaluations guide broker selection by clients. Instead, prior scholarship has primarily assumed clients can rely on a broker’s past performance in determining their future efficacy (Stokes et al. 2013). Established slum leaders can and do rely on prior successes to recruit supporters. However, if clients exclusively privilege past accomplishments, aspiring brokers with no record stand little chance of poaching support from even minimally competent existing leaders. This model predicts a convergence to a low-turnover brokerage environment. We observe the opposite in our field sites, where new leaders constantly surface to compete against—and often displace—existing leaders. Our survey of slum leaders found evidence of new cohorts of leaders and consistent competition among leaders.13 This data aligns with the phenomenon of a bulging class of ambitious yet unemployed Indian youth who often turn to politics to generate income and connections (Jeffrey 2010). These rising leaders can break into the current structure of leadership if they can signal the potential to get things done better than current alternatives. Take Hari Singh, who rose to power by snatching supporters from a preexisting slum leader: [There is] one leader who people stopped following after I came to the slum because I knew more than him…I know everything about the system, whether you go to the Municipal Corporation, Electricity Board, Development Authority, or Collectorate. I know how to solve problems related to these departments. Hence, that leader became less popular.14 The fluid and competitive nature of slum leadership thus affords residents ongoing choices in which slum leader they view as most efficacious.15 What characteristics do residents use to form comparisons of the relative efficacy of the array of leaders—both established and aspiring—who jostle for power in their localities? We argue that clients evaluate efficacy potential via attributes that indicate a broker’s connectivity to actors controlling government benefits, and capability for effectively making claims. 13 Respondents had varying tenure lengths as slum leaders, attesting to the openness of the brokerage environment. The mean tenure length was 20 years, with a standard deviation of just over 10 years. We asked respondents how many slum leaders were in operation when they began slum leadership. Responses indicated a stably competitive environment, with an average of 10.18 competitors for leaders who began more than 25 years ago, and 9.5 competitors for those who began within the past five years. 14 Interview with Hari Singh, June 7, 2016. 15 This assertion also holds for those settlements that emerge through large-scale, preplanned land invasions in which informal leadership is initially present—a type of settlement formation most frequently documented in Latin America (Collier 1976; Gilbert 1998). Scholars describe these settlements as competitive brokerage environments, where new challengers emerge to compete with established slum leaders, affording residents ongoing choice over leader selection (Ray 1969; Gay 1994; Burgwal 1995). 779 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
Adam Michael Auerbach and Tarig Thachil First,clients may prefer brokers with incumbent par- spects.16 First,prior fieldwork informed our selection tisan connectivity,namely ties to the incumbent party of a forced-choice design.Such frameworks better ap- Clients might anticipate such connectivity will help proximate the competitive and voluntary processes brokers access state resources.Indeed,to the degree that define slum leader selection in India.Irrespective top-down models expect clients to have any prefer- of whether they selected leaders through community ences,such incumbent connectivity should head the list. meetings or everyday decisions,slum residents made If client support is a mechanical response to targeted defined choices about whom to seek help from.consis- handouts entirely controlled by party elites,then a bro- tent with our experimental setup. ker's efficacy is largely a function of their ties to these Second,ethnography provided us with a context- elites.However.broker connectivity can also be estab- sensitive way in which to operationalize this se- op//s lished through nonpartisan channels.For example,vot- lection procedure.We presented respondents with ers might prefer brokers with bureaucratic connectivity two hypothetical slum residents running to be pres- to government departments responsible for public ser- ident of a vikas samiti (development committee). vice delivery (Stokes 1995). These neighborhood associations are common orga- Our client-centric perspective also highlights a bro- nizations through which Indian slum dwellers make ker's individual claim-making capabilities in informing claims.7 We leverage the structure of the development their efficacy in lobbying for their clients (Auvero 2000: committee-headed by a president-to ground our ex- Krishna 2002).Prior studies have noted education.in periment in a process of leadership selection familiar to particular,can improve a broker's ability to effectively respondents.Third,our ethnography helped us opera- petition for state services.These studies range from ru- tionalize core concepts into simple,contextually mean- ral India(Manor 2000:Krishna 2002)to Peruvian and ingful candidate attributes.Respondents were given Venezuelan slums (Ray 1969;Stokes 1995).In Indian five pieces of randomized information about each can- slums,Jha,Rao,and Woolcock(2007)also describe in- didate,and then asked to select which would make a formal leaders as well educated.Yet these studies do better leader (full question wording in SI Section S.1) not examine whether this descriptive fact is fueled by Below,we describe how each concept was operational- client preferences for educated leaders,or assess the ized(SI Section S.3 provides the list of treatments). weight of education vis-a-vis other concerns in shaping broker selection. Ethnicity India houses several forms of ethnic categorization. RESEARCH DESIGN Prior studies sometimes use the term "ethnic"to re- fer to single dimensions of ethnicity,notably caste How can we precisely identify the relative weight of (Chandra 2004)or religion (Wilkinson 2004).Here, coethnicity,copartisanship,capability,and incumbent we compare multiple dimensions of ethnicity in slum partisan and bureaucratic connectivity within client leader selection.First,we examine the salience of jatis preferences for brokers?We address this question endogamous subcastes that denote traditional occupa- through a forced-choice conjoint survey experiment.In tions.are highly localized.and number in the hundreds this setup,respondents are presented with information across India.Jatis are nested within broader caste status S5.501g regarding randomized attributes of two slum leaders. groups,indicating whether a jati is considered high or Respondents were then asked which of the two they low caste. prefer. Our treatments varied a leader's name,which indi- This approach has become increasingly popular in cates their subcaste.Respondents were assigned(with the study of political behavior,because it enables re- equal probability)to evaluate a potential slum leader searchers to estimate the causal effects of several treat- from their own jati,8 one of three well-known upper ment components simultaneously (Hainmueller and caste Hindu jatis,one of three well-known lower caste Hopkins 2015).This design also allows us to disentan- Hindu jatis,or one of three well-known Muslim jatis.19 gle the effects of observationally correlated attributes This created a jati match or mismatch between the re- such as caste and party preference.Furthermore,con- spondent and leaders.These names also identified a joint experiments have the potential to reduce socia candidate as Hindu or Muslim.This treatment allowed desirability concerns because they offer respondents us to classify respondents as ethnic matches or mis- the confidentiality of several potential justifications for matches on the broader dimension of religion a decision. Finally,given the multiregional nature of Indian Despite these advantages,we are cognizant of con- slums,we assess the salience of region-of-origin differ- cerns with increasingly complex survey experiments ences by randomizing each leader's home state.Slum These concerns often stem from boilerplate designs that prioritize a researcher's theoretical interest at the 16On ethnographically informed surveys,see Thachil(forthcoming). expense of contextual resonance.Such construct va- 17 See Auerbach(2017). lidity concerns are especially high when working with 18 The respondent's jati was asked at the beginning of the survey.The poorly understood communities. instrument ensured a gap of at least 20 questions between this ques- To improve the validity of our design,we draw tion and the conjoint experiment. We include several jatis within each status level to ensure esti on a combined three years of fieldwork among In- mated effects were not driven by comparisons with any one particu- dia's urban poor to enhance our design in three re- lar jati. 780
Adam Michael Auerbach and Tariq Thachil First, clients may prefer brokers with incumbent partisan connectivity, namely ties to the incumbent party. Clients might anticipate such connectivity will help brokers access state resources. Indeed, to the degree top-down models expect clients to have any preferences, such incumbent connectivity should head the list. If client support is a mechanical response to targeted handouts entirely controlled by party elites, then a broker’s efficacy is largely a function of their ties to these elites. However, broker connectivity can also be established through nonpartisan channels. For example, voters might prefer brokers with bureaucratic connectivity to government departments responsible for public service delivery (Stokes 1995). Our client-centric perspective also highlights a broker’s individual claim-making capabilities in informing their efficacy in lobbying for their clients (Auyero 2000; Krishna 2002). Prior studies have noted education, in particular, can improve a broker’s ability to effectively petition for state services. These studies range from rural India (Manor 2000; Krishna 2002) to Peruvian and Venezuelan slums (Ray 1969; Stokes 1995). In Indian slums, Jha, Rao, and Woolcock (2007) also describe informal leaders as well educated. Yet these studies do not examine whether this descriptive fact is fueled by client preferences for educated leaders, or assess the weight of education vis-à-vis other concerns in shaping broker selection. RESEARCH DESIGN How can we precisely identify the relative weight of coethnicity, copartisanship, capability, and incumbent partisan and bureaucratic connectivity within client preferences for brokers? We address this question through a forced-choice conjoint survey experiment. In this setup, respondents are presented with information regarding randomized attributes of two slum leaders. Respondents were then asked which of the two they prefer. This approach has become increasingly popular in the study of political behavior, because it enables researchers to estimate the causal effects of several treatment components simultaneously (Hainmueller and Hopkins 2015). This design also allows us to disentangle the effects of observationally correlated attributes, such as caste and party preference. Furthermore, conjoint experiments have the potential to reduce social desirability concerns because they offer respondents the confidentiality of several potential justifications for a decision. Despite these advantages, we are cognizant of concerns with increasingly complex survey experiments. These concerns often stem from boilerplate designs that prioritize a researcher’s theoretical interest at the expense of contextual resonance. Such construct validity concerns are especially high when working with poorly understood communities. To improve the validity of our design, we draw on a combined three years of fieldwork among India’s urban poor to enhance our design in three respects.16 First, prior fieldwork informed our selection of a forced-choice design. Such frameworks better approximate the competitive and voluntary processes that define slum leader selection in India. Irrespective of whether they selected leaders through community meetings or everyday decisions, slum residents made defined choices about whom to seek help from, consistent with our experimental setup. Second, ethnography provided us with a contextsensitive way in which to operationalize this selection procedure. We presented respondents with two hypothetical slum residents running to be president of a vikas samiti (development committee). These neighborhood associations are common organizations through which Indian slum dwellers make claims.17 We leverage the structure of the development committee—headed by a president—to ground our experiment in a process of leadership selection familiar to respondents. Third, our ethnography helped us operationalize core concepts into simple, contextually meaningful candidate attributes. Respondents were given five pieces of randomized information about each candidate, and then asked to select which would make a better leader (full question wording in SI Section S.1). Below, we describe how each concept was operationalized (SI Section S.3 provides the list of treatments). Ethnicity India houses several forms of ethnic categorization. Prior studies sometimes use the term “ethnic” to refer to single dimensions of ethnicity, notably caste (Chandra 2004) or religion (Wilkinson 2004). Here, we compare multiple dimensions of ethnicity in slum leader selection. First, we examine the salience of jatis, endogamous subcastes that denote traditional occupations, are highly localized, and number in the hundreds across India. Jatis are nested within broader caste status groups, indicating whether a jati is considered high or low caste. Our treatments varied a leader’s name, which indicates their subcaste. Respondents were assigned (with equal probability) to evaluate a potential slum leader from their own jati, 18 one of three well-known upper caste Hindu jatis, one of three well-known lower caste Hindu jatis, or one of three well-known Muslim jatis. 19 This created a jati match or mismatch between the respondent and leaders. These names also identified a candidate as Hindu or Muslim. This treatment allowed us to classify respondents as ethnic matches or mismatches on the broader dimension of religion. Finally, given the multiregional nature of Indian slums, we assess the salience of region-of-origin differences by randomizing each leader’s home state. Slum 16 On ethnographically informed surveys, see Thachil (forthcoming). 17 See Auerbach (2017). 18 The respondent’s jati was asked at the beginning of the survey. The instrument ensured a gap of at least 20 questions between this question and the conjoint experiment. 19 We include several jatis within each status level to ensure estimated effects were not driven by comparisons with any one particular jati. 780 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
How Clients Select Brokers leaders were randomly assigned to come from the Education is valued because it is seen to improve a respondent's home state,the state of the study city. leader's practical abilities to engage in written claim- another prominent source state within north India's making.22 Our fieldwork unearthed numerous exam- "Hindi belt,"or a prominent source state from a dif ples of claims made through leader-written applica- ferent linguistic region of India. tions.23 For example: The salience of shared jati,faith,or regional iden- tities is provided by the difference in probability of a Since last year we have been suffering from water scarcity. leader being preferred when they are coethnics with a At times,we have to go to the factories or the cremation respondent on that dimension,compared to when they grounds for water...We are in trouble and request that you are not. take action.24 olop//s Each of these treatments assesses the horizontal con- cept of coethnicity.However,ethnic categories also ver- Education also signals a slum leader's ability to navi- tically partition society into groups of unequal status. gate complex state institutions,interact with public offi- In India,lower caste Hindus and Muslims are socioeco- cials,and stay abreast with government policies for the nomically marginalized,relative to upper caste Hindus. urban poor: Our experiment's design allows us to assess how this vertical hierarchy affects respondent preferences.To do I was educated.So I knew about the policies...I was always 4 so,we include dummy variables identifying lower caste in search for any loans with which people could find em- and Muslim leaders ployment and gain something...There are many policies through which our worker brothers can benefit. Partisanship To vary a leader's claim-making capability,we ma- We randomly assign leaders to be affiliated with one nipulated their level of education.Leaders were ran- of the two major parties in our study cities,the In- domly assigned to have no schooling,an eighth grade 4号 dian National Congress (INC)and Bharatiya Janata education,or a college B.A.Our fieldwork confirmed Party (BJP),or to be nonpartisan independents.Co- that each of these manipulations was realistic:our sur- partisanship was then coded by matching leader parti- vey found 40%of slum residents had at least an eighth san profiles with the partisan preferences expressed by grade education and 8.9%had at least some college residents. education.26 This treatment also indicated whether the leader was affiliated with the local incumbent party.Slum lead- (Bureaucratic)Connectivity ers who enjoy such partisan connectivity might find it easier to have requests met.The BJP was the incum- A final attribute we sought to manipulate was per- bent party at the state and municipal levels in our study ceptions of a candidate's connectedness to urban bu- 是 cities.We therefore coded all hypothetical leaders be- reaucracies.Residents may value leaders whom they longing to the BJP as incumbents,those belonging to perceive to be connected with municipal authorities. the Congress as opposition,and the rest as nonpartisan Bureaucratically connected brokers may be regarded independents. as more likely to be informed about the dizzying array of government benefits residents might be eligible for, Capability and better able to pressure municipal personnel into providing benefits. Our fieldwork revealed that slum residents were con- Our fieldwork revealed occupations to be a useful in- cerned with whether a broker possessed the raw capa- dicator of bureaucratic connectivity.The range of jobs bility to lobby public officials. we found Indian slum leaders engaging in enabled re- alistic experimental variations of each leader's job,and We have chosen them as leaders for a reason-they have hence perceptions of their connectivity.We preferred information and knowledge,and perhaps connections,so they should get our work done.20 this conceptualization to several alternatives.First.us ing a treatment that explicitly specified a level of con- nectivity(Candidate A has a high/medium/low level of In interviews,slum leaders underscored how their educational qualifications were often used as a mea- connectivity)can induce social desirability bias.Such evaluative statements that provide an ordering of can- sure of such capabilities: didates carry strong normative connotations that one See,here in the slum,we have only poor people.Most peo- ple are uneducated.So when there is an issue,they need 22 We do not believe education is valued because it signals a resident as wealthier,and hence perhaps more powerful within the city.In help in writing applications.So they began coming to me, fact,education only weakly correlates with household income in our saying brother fill out this application for me...slowly peo- ple told others I do]this kind of work...that's how I built mple(0.192). Figure S.6 provides example slum development council letterhead my early support base.21 stationery used to make claims. 24 Saraswati petition letter,Jaipur,late 2000s 25 Interview with Pramod,an informal leader in Anna Slum,Bhopal 士 20 Interview with Kamal Nagar.Resident 13.August 2017 (June272016). 21 Interview with Sen,an informal leader in Ganpati Slum,Jaipur 23.35%of urban Indians have finished high school,and 12.18% (June1,2016). have finished college(2011 Census of India). 781
How Clients Select Brokers leaders were randomly assigned to come from the respondent’s home state, the state of the study city, another prominent source state within north India’s “Hindi belt,” or a prominent source state from a different linguistic region of India. The salience of shared jati, faith, or regional identities is provided by the difference in probability of a leader being preferred when they are coethnics with a respondent on that dimension, compared to when they are not. Each of these treatments assesses the horizontal concept of coethnicity.However, ethnic categories also vertically partition society into groups of unequal status. In India,lower caste Hindus and Muslims are socioeconomically marginalized, relative to upper caste Hindus. Our experiment’s design allows us to assess how this vertical hierarchy affects respondent preferences.To do so, we include dummy variables identifying lower caste and Muslim leaders. Partisanship We randomly assign leaders to be affiliated with one of the two major parties in our study cities, the Indian National Congress (INC) and Bharatiya Janata Party (BJP), or to be nonpartisan independents. Copartisanship was then coded by matching leader partisan profiles with the partisan preferences expressed by residents. This treatment also indicated whether the leader was affiliated with the local incumbent party. Slum leaders who enjoy such partisan connectivity might find it easier to have requests met. The BJP was the incumbent party at the state and municipal levels in our study cities. We therefore coded all hypothetical leaders belonging to the BJP as incumbents, those belonging to the Congress as opposition, and the rest as nonpartisan independents. Capability Our fieldwork revealed that slum residents were concerned with whether a broker possessed the raw capability to lobby public officials. We have chosen them as leaders for a reason—they have information and knowledge, and perhaps connections, so they should get our work done.20 In interviews, slum leaders underscored how their educational qualifications were often used as a measure of such capabilities: See, here in the slum, we have only poor people.Most people are uneducated. So when there is an issue, they need help in writing applications. So they began coming to me, saying brother fill out this application for me…slowly people told others [I do] this kind of work…that’s how I built my early support base.21 20 Interview with Kamal Nagar, Resident 13, August 2017. 21 Interview with Sen, an informal leader in Ganpati Slum, Jaipur (June 1, 2016). Education is valued because it is seen to improve a leader’s practical abilities to engage in written claimmaking.22 Our fieldwork unearthed numerous examples of claims made through leader-written applications.23 For example: Since last year we have been suffering from water scarcity. At times, we have to go to the factories or the cremation grounds for water…We are in trouble and request that you take action.24 Education also signals a slum leader’s ability to navigate complex state institutions,interact with public officials, and stay abreast with government policies for the urban poor: I was educated. So I knew about the policies…I was always in search for any loans with which people could find employment and gain something…There are many policies through which our worker brothers can benefit.25 To vary a leader’s claim-making capability, we manipulated their level of education. Leaders were randomly assigned to have no schooling, an eighth grade education, or a college B.A. Our fieldwork confirmed that each of these manipulations was realistic: our survey found 40% of slum residents had at least an eighth grade education and 8.9% had at least some college education.26 (Bureaucratic) Connectivity A final attribute we sought to manipulate was perceptions of a candidate’s connectedness to urban bureaucracies. Residents may value leaders whom they perceive to be connected with municipal authorities. Bureaucratically connected brokers may be regarded as more likely to be informed about the dizzying array of government benefits residents might be eligible for, and better able to pressure municipal personnel into providing benefits. Our fieldwork revealed occupations to be a useful indicator of bureaucratic connectivity. The range of jobs we found Indian slum leaders engaging in enabled realistic experimental variations of each leader’s job, and hence perceptions of their connectivity. We preferred this conceptualization to several alternatives. First, using a treatment that explicitly specified a level of connectivity (Candidate A has a high/medium/low level of connectivity) can induce social desirability bias. Such evaluative statements that provide an ordering of candidates carry strong normative connotations that one 22 We do not believe education is valued because it signals a resident as wealthier, and hence perhaps more powerful within the city. In fact, education only weakly correlates with household income in our sample (0.192). 23 Figure S.6 provides example slum development council letterhead stationery used to make claims. 24 Saraswati petition letter, Jaipur, late 2000s. 25 Interview with Pramod, an informal leader in Anna Slum, Bhopal (June 27, 2016). 26 23.35% of urban Indians have finished high school, and 12.18% have finished college (2011 Census of India). 781 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
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. 782
Adam Michael Auerbach and Tariq Thachil trait (and candidate) is more desirable than another. Second, such treatments are abstract, raising the construct validity concerns we sought to avoid. Residents cannot directly observe a leader’s connectivity, and leaders have every incentive to exaggerate their connections. Residents must thus infer a broker’s potential connectivity from observable traits.27 We therefore prefer a nonevaluative and observable measure of connectivity, 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 examples are owners of informal shops catering to residents. Our manipulations include three such jobs: corner 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 vendor, auto rickshaw driver, and unskilled house painter. These professions require residents to circulate outside the slum, providing greater opportunities to gather information about developments within the city than “internal” professions. These jobs indicate an intermediate 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 having 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 municipality 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 manipulations 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 Indian 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 observable trait clients use to infer capability. See Section S.3 for a discussion 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 similarities that facilitate their joint study: both are state capitals, comparably sized, and situated within India’s “Hindi belt.” Third, the authors have conducted a combined 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 constructed by residents in an unsanctioned, unplanned fashion. We isolated a sampling frame of 307 such settlements from the wider slum list through intensive field visits, interviews, and examinations of satellite images. Settlements were then selected through multistage random sampling stratified on population and geographic area. We sampled 20 households per slum by generating Google Earth satellite images for each settlement (Figure S.3). Using a digital drawing program, we measured pixel widths and lengths of each image. We then randomly 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 selected 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 survey 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 theory 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 competitive leadership selection, and the importance of resident agency within such procedures. Migrants first settled Saraswati in the late 1970s to work as miners in nearby stone quarries. The population of the slum now stands at 2,600 residents, and is diverse in caste and regional terms. Saraswati is located 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
How Clients Select Brokers TABLE 1. Descriptive Statistics of Resident Survey Respondents(N=2194) Variables Mean SD Min Max Age 36.57 13.03 17 95 Gender(Female=1) 0.47 0.50 0 1 Years of Education 5.36 5.08 0 18 Literacy (Literate=1) 0.62 0.49 0 1 Monthly Household Income(Rs.) 11.843.75 11.331.84 0 250.000 Born in Slum(Yes =1) 0.27 0.44 0 Years in Slum 22.57 12.69 0.1 75 which became increasingly vigilant in protecting the from the larger appeal of his education and perceived area surrounding the settlement from encroachment in capability.33 4 the mid-2000s.This culminated in the demolition of re- Following the informal election.Jagdish's council pe- cently constructed shanties,after which officials turned titioned officials for public services.An example peti- their attention to reclaiming land lost to earlier waves tion he wrote sought to improve local sanitation: of squatters. In response,residents planned an informal election We have been neglected and that is why it is hell to stay in December 2007 to select a slum president to fight here...You told us before the elections that the sewer line the impending eviction.A group of residents first cre- will be laid,but up until now nothing has been done.Please 4号 ated a list of election rules(Figure S.8),which provide solve this problem.34 insights into their preferences for informal leadership. The rules included that the president should be a slum The construction of leadership in Saraswati illus- resident,work for the settlement's betterment,not en- trates several elements of our research design.First,it gage in antisocial activities,be above 21,and be literate. demonstrates the importance of resident agency and Two residents fought in the election.Jagdish,the preferences in leadership selection,both through in- first candidate,is a high school graduate and a private dividual (Prem)and community selection procedures school teacher in his late 20s.Jagdish is one of the most (Jagdish). educated residents in Saraswati,and a member of the Second.our narrative highlights key attributes res- Berwa jati,a prominent Scheduled Caste [former"un- idents consider in leader selection.The demand for touchable"caste,SC].With a slight frame,quiet confi- educated leaders was woven into Saraswati's elec- dence,and reputation for honesty,Jagdish strays from tion rules.The winner was the more educated can- the thuggish slum leaders depicted in Bollywood films. didate,and the runner-up's base of support stemmed Prem,the second candidate,had been an informal from bureaucratic connectivity.Our narrative also sug- 235.5010 leader in Saraswati for several years.He is a Ra- gests the limits of coethnic support in diverse slums. iput,one of Rajasthan's dominant upper castes.Part of Jagdish's ethnicity may have helped with coethnics, Prem's appeal to residents flowed from his work as a but his victory depended on support from noncoethnic chauffeur for government officials.31 Prem's initial rise residents. in Saraswati illustrates leadership formation through the second pathway we mentioned:everyday decisions RESULTS AND DISCUSSION of residents.There was never a moment in which resi- dents collectively selected him as a leader. We now return to the survey experiment.Our primary On January 8,2008,most adult residents of Saraswati interest is in estimating the average marginal compo- voted in the informal election-almost 800 people in nent effect(ACME):the marginal effect of an attribute total.Jagdish beat Prem,by 458 to 317 votes.Both averaged over the joint distribution of the remaining Jagdish and Prem were supporters of the BJP,and so attributes.Since our attributes were randomized inde- partisan support cannot explain the outcome.Some of pendently,we estimate the AMCEs for all included Jagdish's support stemmed from his coethnic appeal to attributes simultaneously through a simple linear re- SC residents.32 Yet this factor could have only taken gression(Hainmueller,Hopkins,and Yamamoto 2014). him so far within Saraswati,where no one ethnic group Our unit of analysis is a rated profile,and our depen- is especially large.Indeed,support from upper castes, dent variable is coded 1 for leader profiles respondents including Sharma,an influential Brahmin,was cru- preferred within a pair and 0 for those they did not.The cial to Jagdish's success.Instead,his victory stemmed 33 Interviews with Saraswati residents:November 17 2010:January 16,2011.Jagdish himself noted (January 9,2011)that residents de- manded a well-educated leader during a preelection community 31 Interview with Prem,May 21,2011. meeting. 32 Interview with Saraswati residents,January 16 and May 29,2011. 34 Saraswati petition letter,March 2008. 783
How Clients Select Brokers TABLE 1. Descriptive Statistics of Resident Survey Respondents (N = 2194) Variables Mean SD Min Max Age 36.57 13.03 17 95 Gender (Female = 1) 0.47 0.50 0 1 Years of Education 5.36 5.08 0 18 Literacy (Literate=1) 0.62 0.49 0 1 Monthly Household Income (Rs.) 11,843.75 11,331.84 0 250,000 Born in Slum (Yes = 1) 0.27 0.44 0 1 Years in Slum 22.57 12.69 0.1 75 which became increasingly vigilant in protecting the area surrounding the settlement from encroachment in the mid-2000s. This culminated in the demolition of recently constructed shanties, after which officials turned their attention to reclaiming land lost to earlier waves of squatters. In response, residents planned an informal election in December 2007 to select a slum president to fight the impending eviction. A group of residents first created a list of election rules (Figure S.8), which provide insights into their preferences for informal leadership. The rules included that the president should be a slum resident, work for the settlement’s betterment, not engage in antisocial activities, be above 21, and be literate. Two residents fought in the election. Jagdish, the first candidate, is a high school graduate and a private school teacher in his late 20s. Jagdish is one of the most educated residents in Saraswati, and a member of the Berwa jati, a prominent Scheduled Caste [former “untouchable” caste, SC]. With a slight frame, quiet confidence, and reputation for honesty, Jagdish strays from the thuggish slum leaders depicted in Bollywood films. Prem, the second candidate, had been an informal leader in Saraswati for several years. He is a Rajput, one of Rajasthan’s dominant upper castes. Part of Prem’s appeal to residents flowed from his work as a chauffeur for government officials.31 Prem’s initial rise in Saraswati illustrates leadership formation through the second pathway we mentioned: everyday decisions of residents. There was never a moment in which residents collectively selected him as a leader. On January 8, 2008,most adult residents of Saraswati voted in the informal election—almost 800 people in total. Jagdish beat Prem, by 458 to 317 votes. Both Jagdish and Prem were supporters of the BJP, and so partisan support cannot explain the outcome. Some of Jagdish’s support stemmed from his coethnic appeal to SC residents.32 Yet this factor could have only taken him so far within Saraswati, where no one ethnic group is especially large. Indeed, support from upper castes, including Sharma, an influential Brahmin, was crucial to Jagdish’s success. Instead, his victory stemmed 31 Interview with Prem, May 21, 2011. 32 Interview with Saraswati residents, January 16 and May 29, 2011. from the larger appeal of his education and perceived capability.33 Following the informal election, Jagdish’s council petitioned officials for public services. An example petition he wrote sought to improve local sanitation: We have been neglected and that is why it is hell to stay here…You told us before the elections that the sewer line will be laid, but up until now nothing has been done. Please solve this problem.34 The construction of leadership in Saraswati illustrates several elements of our research design. First, it demonstrates the importance of resident agency and preferences in leadership selection, both through individual (Prem) and community selection procedures (Jagdish). Second, our narrative highlights key attributes residents consider in leader selection. The demand for educated leaders was woven into Saraswati’s election rules. The winner was the more educated candidate, and the runner-up’s base of support stemmed from bureaucratic connectivity. Our narrative also suggests the limits of coethnic support in diverse slums. Jagdish’s ethnicity may have helped with coethnics, but his victory depended on support from noncoethnic residents. RESULTS AND DISCUSSION We now return to the survey experiment. Our primary interest is in estimating the average marginal component effect (ACME): the marginal effect of an attribute averaged over the joint distribution of the remaining attributes. Since our attributes were randomized independently, we estimate the AMCEs for all included attributes simultaneously through a simple linear regression (Hainmueller,Hopkins, and Yamamoto 2014). Our unit of analysis is a rated profile, and our dependent variable is coded 1 for leader profiles respondents preferred within a pair and 0 for those they did not.The 33 Interviews with Saraswati residents: November 17, 2010; January 16, 2011. Jagdish himself noted (January 9, 2011) that residents demanded a well-educated leader during a preelection community meeting. 34 Saraswati petition letter, March 2008. 783 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
Adam Michael Auerbach and Tarig Thachil FIGURE 1.Effect of Broker Attributes on Probability of Being Preferred for Development Council Presidency 000100006/LLoL Broker Caste Same as Resident- Different from Resident- Broker Religion Same as Resident- Different from Resident- Broker State Same as Resident- Different from Resident- Broker Ethnic Rank Muslim Leader Scheduled Caste Leader- Upper Caste Leader Broker Partisanship Same as Resident- Different from Resident- Broker Incumbent Status Incumbent- Opposition- Independent- Broker Connectivity(Job) 4号元 High(Municipal Job)- Medium(Outside Slum)- Low (Inside Slum)- Broker Capability (Education) Modum High(College BA) Low(None) -2 .1 0 1 Effect on Pr(Being Selected as Slum President) 是 Notes:This plot shows estimates of the effects of the randomly assigned slum leader attribute values on the probability of being preferred for president of the slum development council.Estimates are based on an OLS model with standard errors clustered by respondent detailed in SI Table S.1;bars represent 95%confidence intervals.The points without horizontal bars denote the attribute value that is the reference category for each attribute. independent variables are dummy variables for each nate against leaders from Muslim groups(-9.8 pp,p< attribute.We cluster standard errors by respondent. 0.000),relative to upper caste Hindus.Scheduled Caste leaders were also disfavored,but not significantly so Main Results (-2.6 pp,p =0.212).We will later unpack this discrim- ination result. Figure 1 shows how each attribute affects the likeli- Our next set of results concern the impact of a hood of a leader being preferred to serve as president leader's partisan affiliation.We find residents favor of the slum development committee.The figure dis- copartisan leaders(76 pp,p<0.000),consistent with plays both the AMCEs(points)and the 95%confi- prior studies of India's countryside (Dunning and dence intervals(bars).35 Nilekani 2013).Interestingly,residents do not favor First,we find that ethnic identities structuring village leaders who are affiliated to the local incumbent life remain politically salient within urban slums.Slum party,relative to independent,nonpartisan candidates residents prefer leaders who come from the same jati (-1.3 pp,p=0.505).We also do not find residents pre- (6.4 percentage points(pp),p =0.002)and religion(71 ferring brokers with opposition party affiliations to pp,p<0.000)to those who do not.Second,we find independent brokers (0.8 pp,p=0.683).Thus,inde- region-of-origin divisions that have not structured rural pendent brokers do not face a disadvantage relative politics prove salient among urban populations(8.7 pp. to party-affiliated brokers.This result cuts against top- p<0.000).36 Third,we find slum residents discrimi- down theories that expect a broker's efficacy to stem largely from party approval.These findings also suggest that partisanship plays a greater role as an indicator of 35 Full regression results for reported in Table S.1. distributive inclusion than as an indicator of efficacy in 36 All p-values reported here are for two-sided tests. securing resources. 784
Adam Michael Auerbach and Tariq Thachil FIGURE 1. Effect of Broker Attributes on Probability of Being Preferred for Development Council Presidency Same as Resident Different from Resident Same as Resident Different from Resident Same as Resident Different from Resident Muslim Leader Scheduled Caste Leader Upper Caste Leader Same as Resident Different from Resident Incumbent Opposition Independent High (Municipal Job) Medium (Outside Slum) Low (Inside Slum) High (College BA) Medium (8th Grade) Low (None) Broker Caste Broker Religion Broker State Broker Ethnic Rank Broker Partisanship Broker Incumbent Status Broker Connectivity (Job) Broker Capability (Education) -.2 -.1 0 .1 .2 Effect on Pr(Being Selected as Slum President) Notes: This plot shows estimates of the effects of the randomly assigned slum leader attribute values on the probability of being preferred for president of the slum development council. Estimates are based on an OLS model with standard errors clustered by respondent detailed in SI Table S.1; bars represent 95% confidence intervals. The points without horizontal bars denote the attribute value that is the reference category for each attribute. independent variables are dummy variables for each attribute. We cluster standard errors by respondent. Main Results Figure 1 shows how each attribute affects the likelihood of a leader being preferred to serve as president of the slum development committee. The figure displays both the AMCEs (points) and the 95% confidence intervals (bars).35 First, we find that ethnic identities structuring village life remain politically salient within urban slums. Slum residents prefer leaders who come from the same jati (6.4 percentage points (pp), p = 0.002) and religion (7.1 pp, p < 0.000) to those who do not. Second, we find region-of-origin divisions that have not structured rural politics prove salient among urban populations (8.7 pp, p < 0.000).36 Third, we find slum residents discrimi- 35 Full regression results for reported in Table S.1. 36 All p-values reported here are for two-sided tests. nate against leaders from Muslim groups (−9.8 pp, p < 0.000), relative to upper caste Hindus. Scheduled Caste leaders were also disfavored, but not significantly so (–2.6 pp, p = 0.212). We will later unpack this discrimination result. Our next set of results concern the impact of a leader’s partisan affiliation. We find residents favor copartisan leaders (7.6 pp, p < 0.000), consistent with prior studies of India’s countryside (Dunning and Nilekani 2013). Interestingly, residents do not favor leaders who are affiliated to the local incumbent party, relative to independent, nonpartisan candidates (–1.3 pp, p = 0.505). We also do not find residents preferring brokers with opposition party affiliations to independent brokers (0.8 pp, p = 0.683). Thus, independent brokers do not face a disadvantage relative to party-affiliated brokers. This result cuts against topdown theories that expect a broker’s efficacy to stem largely from party approval.These findings also suggest that partisanship plays a greater role as an indicator of distributive inclusion than as an indicator of efficacy in securing resources. 784 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
