Download Weiss Past Recipients - University of California, Berkeley

Weiss Family Program Fund
Spring 2015 Recipients
A Note about the Sponsor: The goal of the Weiss Family Program Fund, and its funder, Child Relief
International, is to sponsor graduate student and faculty research that will positively affect the lives of
poor people in poor countries. Projects must contribute to development economics, broadly defined, and
may address a wide range of issues that affect less developed countries. Included below are summaries of
the four UC Berkeley-lead research projects funded in spring 2015.
Worker Safety in Bangladesh (Edited Excerpt)
Laura Boudreau
PhD Student, Business and Public Policy
Background
Poor workers in developing countries generally work in harsh and often unsafe conditions. The
prospective benefits to workers of improved working conditions are obvious: psychological, cognitive, and
physical benefits could improve many aspects of their and their families' quality of life. For firms,
healthier and happier workers may generate productivity gains and increase worker retention. But
improving working conditions is also costly to firms and may ultimately lead to adverse general
equilibrium effects on employment and growth. Research on this topic will have important policy
implications for labor standards, management practices, and corporate social responsibility initiatives.
Hypothesis
This research project evaluates whether giving poor workers a voice within the firm, specifically a say on
workplace safety, improves worker and firm outcomes. It is hypothesized that (a) poor management
practices may impede information sharing about safety between workers and managers that could
benefit workers and be productive for the firm; (b) the establishment of an institution to aggregate and
communicate workers' safety preferences to management may alleviate informational constraints and
thus generate more and better targeted investments in safety that ultimately benefit workers and the
firm.
Study Design
The research design will take advantage of a phased roll-out of an Occupational Health and Safety (OSH)
Committee Program to improve worker safety in the Bangladesh ready-made garment (RMG) sector.
Identification strategy relies on comparison of outcomes pre- and post-roll-out at factories randomly
selected to participate in the first phase of the Program with factories randomly selected to participate in
the second and third phases.
Worker- and factory-level outcomes will be compared across treatment and control factories. Workerlevel outcomes are currently grouped into as follows: (1) OSH knowledge and empowerment; (2)
Psychological and physical well-being; (3) Labor supply and cognitive ability; and (4) Household outcomes.
Factory-level outcomes are currently grouped as follows: (1) OSH performance; (2) Productivity, wages,
and overall financial performance; and (3) Management-worker relations.
Weiss Family Program Fund
Spring 2015 Recipients
Detecting Social Networks with Satellite (Edited Excerpt)
Solomon Hsiang, Associate Professor of Public Policy, UC Berkeley
Jeremy Magruder, Associate Professor of Agricultural and Resource Economics, UC Berkeley
Background
It is becoming increasingly clear that development interventions can improve their effectiveness by
targeting “the right” individuals within a local social network (Banerjee et al., 2013; Beaman et al., 2014).
For example, in training programs that teach individuals in a village how to use a new technology, if
researchers target individuals more central in the network for training then learning diffuses rapidly in
comparison to random targeting.
A challenge to applying this insight widely in development interventions is the high cost associated with
mapping social networks within rural villages. To date, social networks in remote village contexts have
only been constructed using costly, detailed surveys where respondents explicitly identify links in the
networks. The researchers propose that the cost of estimating social network structure can be
dramatically reduced by taking advantage of pre-existing satellite data and various spatial modeling
techniques.
Hypothesis
The researchers hypothesize that (a) key network features can be predicted probabilistically using publicly
available satellite images; (b) that this prediction algorithm can be automated to require no on-theground survey; (c) prediction quality can be sufficiently high that its use in rural development
interventions increases their efficacy—demonstrated here mainly through simulation.
Study Design
A low cost model to estimate social networks in a group could exploit pre-existing spatial data describing
settlement patterns and the environmental context in which the group lives. By linking detailed network
data from over 200 villages in Malawi and India (that have already been surveyed) with satellite data, the
researchers will explore whether it is possible to predict social network structure within a village using
only satellite data.
Weiss Family Program Fund
Spring 2015 Recipients
Externalities and Social Influence in Childhood Immunization (Edited Excerpt)
Anne Karing
PhD student, Economics
Background
Childhood immunization is one of the most effective ways to reduce under-five mortality. Significant
progress has been made in making vaccines free and readily available in developing countries. While
some caregivers fail to initiate vaccination for their children, more frequently, caregivers begin
immunization but then neglect later rounds. Qualitative research in Pakistan and Sierra Leone show that
most people do not know about the externalities from vaccinating. Caregivers think of childhood
immunization as being beneficial only to the child that receives the vaccine.
Study Design
The evaluation will use a randomized design with a community as the unit of treatment. The first
treatment educates caregivers about the externalities from vaccination. The second treatment provides
information about the share of currently vaccinated children. The different information treatments will
be provided by frontline health workers (FHWs) e.g. vaccinators, Lady Health Workers and midwives.
Hypothesis
The researcher is interested in testing whether altruistic preferences or the propensity to free-ride are
strong enough to increase or decrease immunization coverage and timeliness.
The researcher is further interested in understanding the role of providing information about the share of
people immunizing. The researcher hypothesizes that treatment caregivers told about the share of
people vaccinating their children could increase take-up and provide evidence of social learning and
herding behavior. When interacting “share” treatments with the externality treatment, researchers are
able to test for a mechanism of conditional cooperation: are people more likely to contribute to the
public good when a higher share of their community is doing the same? If people’s decision to vaccinate,
however, is primarily driven by the externality information we get the opposite prediction: caregivers
should be more likely to vaccinate their child if fewer people around them vaccinate, and have a lower
incentive to vaccinate their child if the share of other people vaccinating is high.
The experiment will address important economic and policy questions: What happens as people learn
about externalities? Can social encouragements be used to improve the efficacy of the understanding of
the externality? To what extent can care-givers be influenced by other people’s behavior? This study will
be a first step in a larger research agenda that the researcher plans to pursue on the role of social
influence in childhood immunization.
Weiss Family Program Fund
Spring 2015 Recipients
Estimating the Impacts of Rural Electrification in Kenya (Edited Excerpt)
Catherine Wolfram
Cora Jane Floor Professor of Business Administration at the Haas School of Business and Faculty Director
of the Energy Institute at Haas
Background
Over two-thirds of the population of Sub-Saharan Africa is still without access to electricity. While
electrification is an important goal for many governments in this region, there are many other priorities
that require funding, including public health, education, sanitation, and safety. This research seeks to
understand the most cost-effective ways to increase energy access and the social and economic impacts
of electrification.
While previous work has analyzed the impacts of electrification using non-experimental methods, this
project will be the first large-scale randomized evaluation of rural electrification. It is differentiated by its
larger sample size, clustered design which controls for spillovers, and wider set of social and economic
outcomes of interest. Precise estimates of the impacts of electrification can help promote a number of
development goals.
Hypothesis
We hypothesize that bringing electricity to rural households in Kenya will lead to economically significant
changes in household income and assets, children’s education, time use, and energy consumption. Past
studies suggest that the benefits of rural electrification are significant (see, e.g., Lipscomb, et al., 2013).
Women and children receive many of the gains associated with rural electrification, as they often benefit
disproportionately from improved indoor living conditions and increased appliance use (Dinkelman 2011).
Study Design
This study will build on a substantial amount of work that has already been completed by University of
California, Berkeley researchers, in partnership with the Rural Electrification Authority (REA). As a result of
this unique partnership with Kenyan government, the foundation for a randomized evaluation of
electricity infrastructure is now in place. Specifically, electricity connection vouchers (worth varying
amounts) were randomly assigned to clusters of rural households in Western Kenya. Households
accepting these vouchers were then connected to the national grid by REA, in cooperation with the
country’s main utility, Kenya Power.
Follow-up surveys with the 2,504 households in the sample will be conducted to estimate the impacts of
electrification. The researcher will administer a similar survey to measure impacts by comparing
outcomes at treatment and control households. Outcomes of interest include: household income and
assets, female employment, children’s education, time use, and energy consumption, in addition to other
variables. Ideally, spillovers to unconnected households in treatment communities will also be measured
to obtain more precise household-level estimates of the impacts of electrification.