 The project consists of a set of five papers anchored by a field experiment in Bangalore, India. Three of the papers represent collaborations with Isha Ray (Associate Professor, Energy and Resources Group, U.C. Berkeley). This research has been funded by Berkeley's Development Impact Laboratory under USAID Cooperative Agreement AID-OAA-A-13-00002. Please do not hesitate to contact me if you would like to read one of these papers. PAPERS
“Flows, Leaks, and Blockages in Informational Interventions: Field Experimental Evidence from Bangalore's Water Sector” 2018. World Development.
106: 149-160.
(with Tanu Kumar and Isha Ray) Can providing citizens with information compensate for unreliable public services?
Existing scholarship examines whether increasing transparency motivates individuals to
hold governments accountable. No one, however, has studied whether information that
increases service predictability reduces coping costs or changes how citizens relate to the
state. We conducted a field experimental evaluation of a program providing households
in Bangalore with advance warning of the timing of intermittently provided water
services. Contrary to expectations, we detected no impacts on household welfare, citizen
attitudes about the state utility, or propensities to contact the state utility directly rather
than through intermediaries. Noncompliance by street-level bureaucrats charged with
supplying water timing information both reduced the power of the experiment and
undermined the program’s viability. These findings suggest that scholars should
investigate and report how frontline worker actions drive positive or null experimental
findings. We introduce a framework for analyzing “information pipelines” to assist with
such efforts.
“Frontline Worker Compliance with Transparency Reforms: Barriers Posed by Family and Financial Responsibilities” (with Christopher Hyun and Isha
Ray) 2018. Governance. 31: 65-83. (Formerly "Why Street Level Bureaucrats Don't Comply: Insights from the Valvemen of Bangalore") Significant
development funding flows to informational interventions intended to improve
public services. Such “transparency fixes” often depend on the cooperation of
frontline workers who produce or disseminate information for citizens. This
article examines frontline worker compliance with a transparency intervention
in Bangalore’s water sector. Why did
compliance vary across neighborhoods, and why did workers exhibit modest rates
of compliance overall? Drawing on ethnographic observation and an original
dataset, this article finds that variation in workers’ family responsibilities
and financial circumstances largely explains variation in compliance with the
intervention. Furthermore, workers often prioritize longstanding
responsibilities over new tasks seen as add-ons, leading to modest rates of
compliance overall. Perceptions of
“core” jobs can be sticky—especially when reaffirmed through interactions with
citizens. This study represents one of the first multi-method companions to a
field experiment, and illustrates how the analysis of qualitative and
observational data can contribute to impact evaluation.
“Crowd-Sourced Data for
Comparative Politics: Insights from Urban India.” Forthcoming. Studies in Comparative International Development. (with Anustubh Agnihotri and
Christopher Hyun) In much of the developing world, states fail to collect accurate information on social and
political phenomena such as protest activity, the extent and reach of public services, and
corruption. Crowd-sourced data—data sourced electronically from disparate individuals
or groups—now offers researchers new information that can potentially correct for biases
in existing data about such processes. In this paper, we highlight ways in which crowd-
sourced data can be used to cast new light on major problems in comparative politics and
show how important analytic pitfalls can be avoided. Descriptive inference using crowd-
sourced data can be improved by explicitly examining how data is contributed and
conducting ground truthing exercises. Assessments of the causal impact of crowd-
sourced data on political processes can be strengthened by randomizing exposure at the
cluster rather than individual level, or by measuring information spillovers. We illustrate
strategies for addressing inferential difficulties in urban India, through a study of the
collection of crowd-sourced information on water delivery. In this study, crowd-sourced
data on water allocation is used to revisit long-standing debates on distributive politics
and newer debates regarding the potential effects of informational interventions on
citizen political participation. “Distributive Politics in
Networked Systems: The Political Geography of Water Intermittency” (with Tanu
Kumar, Megan Otsuka, Francesc Pardo-Bosch, and Isha Ray) (in preparation)
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