Disempowered: Electricity, Citizenship, and the Politics of Privatization in South Asia a Thesis Submitted to the Faculty Of

Disempowered: Electricity, Citizenship, and the Politics of Privatization in South Asia a Thesis Submitted to the Faculty Of

Disempowered: Electricity, Citizenship, and the Politics of Privatization in South Asia A Thesis submitted to the Faculty of the Graduate School of Arts and Sciences of Georgetown University in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Government By Erum Aly Haider, M.A. Washington, DC April 7, 2020 Copyright c 2020 by Erum Aly Haider All Rights Reserved ii Disempowered: Electricity, Citizenship, and the Politics of Privatization in South Asia Erum Aly Haider, M.A. Thesis Advisor: Irfan Nooruddin, Ph.D. Abstract The ability to maintain political control over public goods is at the heart of the debate on distributive politics. Scholarship on patronage suggests that citizens’ dependence on political representatives for selective benefits leads to a perverse form of accountability. The privatization of service delivery is offered as a potential solution to remove debilitating effects of political influence on economic distribution. However, I argue that privatization can diminish the ability of citizens to voice dissatisfaction with public goods, and to be substantively represented by the state. I find that the economic redistributive effects notwithstanding, the political effects of privatization are under-theorized. This study uses the case of electricity privatization in Pakistan to answer the question - what happens to the relationship between citizens and their representatives, when the latter no long influence distributive outcomes? I suggest first that privatization diminishes the ability of citizens to use political representatives to lobby for better provision. Next, I argue that being ‘stuck’ in low-provision neighborhoods makes individuals less likely to exercise their political power overall, even for non-privatized public goods. Finally, I propose that the mechanism by which this happens is the diminishing of inter-personal and institutional trust, as a consequence of households blaming their neighbors, and not the state or its subsidiaries, for poor service delivery. Over twelve months of qualitative research in Karachi, Pakistan, are used to generate these hypotheses and identify potential causal mechanisms. A unique spatial dataset of iii 25,000 service delivery clusters across the city, and an original survey and survey experiment (N≈1000) are used to quantitatively test each part of my theory. I find that a virtuous cycle of trust between private institutions and consumers can create efficiencies in the consumption of scarce resources, and provide important psychic benefits. Conversely, a cycle of mistrust can create uncertainty that spills over into the political sphere. This work joins emergent scholarship that suggests that patronage in hyper-local contexts, far from being a one-way relationship between powerful state actors and powerless clients, is an important feedback loop for citizens to express priorities, preferences and satisfaction within and beyond the electoral cycle. Index words: Political economy, Electricity, Electoral politics, Pakistan, South Asia, Urban politics, Privatization iv Acknowledgments This work was funded by the American Institute for Pakistan Studies and the Georgetown Graduate School of Arts and Sciences travel and dissertation research grants. The survey in Karachi that was conducted between January 2018 and April 2019 was funded by the International Growth Center at the LSE, UK and implemented by Gallup, Pakistan. This project was also supported by the United States Institute of Peace (USIP) Jennings Randolph Peace Scholar Award. I gratefully acknowledge and thank all these organizations for funding and supporting my work; the views expressed here are those of the author alone and do not reflect the views of these organizations. Thank you to my committee: Irfan Nooruddin, Marko Klašnja, Mubbashir Rizvi and Rajesh Veeraraghavan, without whose patient guidance, feedback and encouragement this project would not be possible. Thanks to faculty and friends at Georgetown University’s Government department for providing multiple opportunities to present chapters of this work over the last six years, thanks in particular to Charles King, Desha Girod and Nita Rudra for their mentorship. Thank you to Adam Auerbach, Tariq Thachill, Gabrielle Kruks-Wisner and Alison Post for reading this work at various stages and providing invaluable feedback. A very special thanks to Milan Vaishnav and the members of the India Politics workshop in Washington D.C., for making the city one of the best places to study and present work on the South Asian subcontinent. v I want to express immense gratitude for my cohort: Inu Manak, Shubha Kamala Prasad, Alex Podkul, Caitlin McGowan, Jeff Poushter, DongJoon Park, Nik Kalyanpur, Kristen Collins and Andrew Szarejko. You are the best colleagues anyone could ask for. Thank you to the colleagues and friends from other departments and schools who’ve seen this work evolve over the years: Madhulika Khanna, Rabea Kirmani, Paula Ganga, Saad Gulzar, Mashail Malik, Niloufer Siddiqui and Sarah Khan. Thank you to Zaineb Majoka and Ali Hamza, and to Sauleh Siddiqui and Lacey Johnson, for making Washington, D.C my second home. A very special thanks to Ahsan Butt, for failing to convince me not to apply to graduate school. In Pakistan, I am grateful for the friendship and guidance of Nida Kirmani, Umair Javed, Sameen Mohsin Ali and others at the Lahore University of Management Sciences. I am grateful to Nausheen Anwar, Noman Ahmad and Gulraiz Khan at IBA, NED and Habib University in Karachi. Thank you to Khurram Hussain and Faiza Mushtaq, for being constant mentors and supporters of this project. Thank you to Zia-ur-Rehman and Abubakar Baloch for your wealth of knowledge, and for helping me navigate Karachi’s neighborhoods. I am grateful to the geographers and statisticians at the Census Bureau in Sindh and at the Orangi Pilot Project, and to the librarians at the Dawn News Library at Haroon House and the Sindh Archives. I thank Mutaher Khan for his excellent assistance with data entry and research. This project would not be possible without the individuals and communities in Karachi and Lahore who invited me into their homes, who took out the time to speak with me and my team of enumerators. Thank you. Thank you to Samira Hussain, to the Sultanalis and the Peermohommads for your unwavering support and faith in me. My thanks and love to Asad Rehman, for his wisdom and years of tech support. My love to Ammara, Asad, and Mehreen, and vi to my dearest Chris, and to your families. You’ve provided me with a place to write, and powered me through these years with humor, kindness, and tea. I can never thank you enough. This work is dedicated to my family: to Nani, my mother and father, and to Sara and Shaan. Your love and support has made this possible. vii Table of Contents Chapter 1 Introduction . .1 1.1 Electricity in urban Pakistan . .3 1.2 State-making and political embeddedness . .5 1.3 Patronage, citizenship and a language of rights . .8 1.4 Alternative hypotheses and tests . 14 1.5 Research design and methodology . 16 1.6 A roadmap . 17 2 The new politics of doing business in a developing megacity . 20 2.1 ‘Everyone is stealing’: Politics and state provision . 20 2.2 Political mobilization and the welfare state . 31 2.3 City planning and political subjectivity . 37 2.4 Post-privatization: Segregated citizenship in Karachi . 49 2.5 Discussion . 53 2.6 Conclusion . 58 3 Participation and citizenship in privatized service delivery regimes . 64 3.1 ‘What can they do about it?’ . 64 3.2 Existing literature and theoretical expectations . 69 3.3 Hybrid service delivery in practice . 74 3.4 Expectations, efficacy and entitlement . 83 3.5 State embeddedness and private service delivery . 95 3.6 Discussion . 98 3.7 Conclusion . 103 4 Disempowered: Political trust and service delivery . 112 4.1 ‘Paying Bacha’ for the bills . 112 4.2 Stealing from your brother: The invention of ‘theft’ . 119 4.3 Priming on theft: A survey experiment . 124 4.4 Survey and service delivery data . 127 4.5 Institutional and inter-personal trust . 136 4.6 Discussion . 139 4.7 Conclusion . 142 5 Conclusion . 149 viii 5.1 ‘Nothing gets fixed if you don’t go in a group’ . 149 5.2 Summary of findings . 152 5.3 Theoretical contributions and policy implications . 154 Bibliography ................................... 156 ix List of Figures 2.1 An example of a pirated connection bill . 60 2.2 An electricity transformer with pirated connections . 62 2.3 Example of K-Electric advertisement from 2010 . 63 3.1 Quality of private services: Electricity outage by District . 76 3.2 Ranked means of service delivery priorities . 105 3.3 Service delivery in Karachi, 1998-2018 . 106 3.4 Electricity transformers in District South, Karachi . 107 3.5 Electricity bills and household income . 108 3.6 Complaint and claim-making . 109 3.7 Political embeddedness and stratification: Marginal effects . 111 4.1 Trust and service delivery: High and low outage areas . 131 4.2 Trust and service delivery: Proximate neighborhoods . 132 4.3 Advertisement campaign for Karachi Electric Supply Corp., c. 2009 . 148 x List of Tables 1.1 Privatization and political outcomes . 10 1.2 Privatization, stratification and political outcomes . 13 1.3 Service delivery and political participation . 14 2.1 Consumption of electricity by sector, percentage total sales . 39 2.2 Class, privatization and claim-making: Survey results . 61 3.1 Theoretical expectations of privatized service delivery . 71 3.2 The quality of service delivery and outage . 80 3.3 Comparing high and low quality service neighborhoods . 88 3.4 Comparing very low quality service neighborhoods . 93 3.5 Mechanisms summary . 100 3.6 Service delivery and political participation . 110 4.1 Privatization, stratification and political outcomes . 124 4.2 Trust, voting and participation . 143 4.3 Trust, voting and participation: Spatially clustered . 144 4.4 Experiment results .

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