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We conduct two experiments to identify the value parents place on equality of opportunity when investing in children. The experiments exogenously vary short-run returns to educational investments to identify the weight placed on equalizing “opportunity” (child-level investment) relative to maximizing “returns” (total household earnings) or to equalizing “outcomes” (child-level expected earnings). While parents in both experiments place some weight on maximizing returns, they also display a strong preference for equalizing opportunities and are willing to forgo 15–45 percent of their earnings to do so. Parents in higher-income countries also care about equalizing outcomes, while parents in lower-income countries do not. (JEL D63, J12, J13, O15) 

How does the expectation that a child will receive government benefits in adulthood affect parental investments in the child’s human capital? Most parents whose children receive Supplemental Security Income (SSI) benefits overestimate the likelihood that their child will receive SSI benefits in adulthood. We present randomly selected families with the predicted likelihood that their child will receive SSI benefits in adulthood. Reducing parents’ expectations that children will receive benefits in adulthood does not increase investments in children’s human capital. This zero effect is precisely estimated. Likely explanations include parents working more themselves, nonfinancial goals influencing investment, and families facing investment constraints. (JEL G52, I26, I38, J13, J24, J31) 

Management of deep-sea fisheries in areas beyond national jurisdiction by Regional Fisheries Management Organizations/Arrangements (RFMO/As) requires identification of areas with Vulnerable Marine Ecosystems (VMEs). Currently, fisheries data, including trawl and longline bycatch data, are used by many RFMO/As to inform the identification of VMEs. However, the collection of such data creates impacts and there is a need to collect non-invasive data for VME identification and monitoring purposes. Imagery data from scientific surveys satisfies this requirement, but there currently is no established framework for identifying VMEs from images. Thus, the goal of this study was to bring together a large international team to determine current VME assessment protocols and establish preliminary global consensus guidelines for identifying VMEs from images. An initial assessment showed a lack of consistency among RFMO/A regions regarding what is considered a VME indicator taxon, and hence variability in how VMEs might be defined. In certain cases, experts agreed that a VME could be identified from a single image, most often in areas of scleractinian reefs, dense octocoral gardens, multiple VME species’ co-occurrence, and chemosynthetic ecosystems. A decision flow chart is presented that gives practical interpretation of the FAO criteria for single images. To further evaluate steps of the flow chart related to density, data were compiled to assess whether scientists perceived similar density thresholds across regions. The range of observed densities and the density values considered to be VMEs varied considerably by taxon, but in many cases, there was a statistical difference in what experts considered to be a VME compared to images not considered a VME. Further work is required to develop an areal extent index, to include a measure of confidence, and to increase our understanding of what levels of density and diversity correspond to key ecosystem functions for VME indicator taxa. Based on our results, the following recommendations are made: 1. There is a need to establish a global consensus on which taxa are VME indicators. 2. RFMO/As should consider adopting guidelines that use imagery surveys as an alternative (or complement) to using bycatch and trawl surveys for designating VMEs. 3. Imagery surveys should also be included in Impact Assessments. And 4. All industries that impact the seafloor, not just fisheries, should use imagery surveys to detect and identify VMEs. 

Schools worldwide distribute information to parents about their children’s academic performance. Do frictions prevent parents, particularly low-income parents, from accessing this information to make decisions? A field experiment in Malawi shows that, at baseline, parents’ beliefs about their children’s academic performance are often inaccurate. Providing parents with clear, digestible performance information causes them to update their beliefs and adjust their investments: they increase the school enrollment of their higher-performing children, decrease the enrollment of lower-performing children, and choose educational inputs that are more closely matched to their children’s academic level. Heterogeneity analysis suggests information frictions are worse among the poor. (JEL C93, D83, I21, I24, J13, O15)