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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.