Risk and development: an experimental study of insurance demand and risky decision making in rural Uganda

Uninsured risk leaves poor households in developing countries vulnerable to serious negative shocks hard to cope with, and forces them to engage in costly risk management strategies to hedge against their occurrence. Although mutual support networks have long existed, they are ill-suited to protect against covariate or catastrophic risks. Grounded in a strong rationale, insurance has however failed to fulfil its potential, plagued by serious informational and enforcement problems. Nevertheless, in recent years a new form of index-based insurance has arisen as a promising instrument to deliver formal coverage, overcoming the mentioned issues through its particular design. Yet index insurance is not without problems, its key limitation is the imperfect correlation between index and losses (i.e. basis risk), a problem that partially explains the low demand it has been met with. Some recent papers argue that informal risk sharing can complement the coverage of index insurance, by partially absorbing basis risk. However, the possibility that pre-existing risk-sharing arrangements hamper formal insurance uptake cannot be dismissed. To shed light on this relationship and the future of index insurance, the paper investigates how the provision of formal insurance interacts with pre-existing risk-sharing arrangements, employing experimental evidence from a rural area in eastern Uganda. We contribute by varying exogenously actual risk sharing-to study its effect on insurance demand-and insurance characteristics-to test whether this effect varies depending on the type of insurance. In addition, we investigate the influence that the provision of formal insurance exerts on risk sharing behaviour. We find that anticipated informal risk sharing crowds out demand for index insurance, but does not affect indemnity insurance uptake. This result is partly explained by the risk sharing behaviour observed

Lab and life: Does risky choice behaviour observed in experiments reflect that in the real world?

Risk preferences play a crucial role in a great variety of economic decisions. Measuring risk preferences reliably is therefore an important challenge. In this paper we ask the question whether risk preferences observed in economic experiments reflect real-life risky choice behaviour. We investigate in a sample representative for a rural region of eastern Uganda whether pursuing farming strategies with both a higher expected profit and greater variance of profits is associated with willingness to take risks in an experiment. Controlling for other determinants of risk-taking in agriculture, we find that risky choice behaviour in the experiment is correlated with risky choice behaviour in real life in one domain, i.e. the purchase of fertiliser, but not in other domains, i.e. the growing of cash crops and market-orientation more broadly. Our findings suggest that economic experiments may be good at capturing real-world risky choice behaviour that is narrowly bracketed

Combining service design and discrete choice experiments for intervention design: An application to weather index insurance

In this paper we provide a detailed description of the methodological steps involved in conducting a Service Design study in combination with Discrete Choice Experiments (DCEs). It complements the conceptual and epistemological argument developed for this methodological combination in Osborne et al. (2021, World Development, in review WD-19535). Service Design for the co-creative development of policy interventions in complex adaptive systems involves an iterative process of moving between the six methodological stages of (1) problem co-definition, (2) actor-centred mapping, (3) experience-based problem diagnosis, (4) rapid prototyping, (5) design and testing and (6) upscaling. We suggest using DCEs as a quantitative method that is contextually adaptable and comparatively fast and cheap to implement, as part of stage (6) design and testing. Whilst both methods can operate independently with their own strengths and limitations, we find their combination to add value to the processes and outcomes of each. We illustrate the general methodological approach with a step-by-step description of its application to Weather Index Insurance in eastern Uganda

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Co-producing policy recommendations: Lessons from a DEGRP project in Uganda

As part of their research on agricultural investment in Uganda, DEGRP grant holders from the University of East Anglia conducted a series of consultations with local and national stakeholders. The aim? To gain feedback on the relevance of their research findings, test the applicability of their policy recommendations, and boost the overall likelihood of policy impact. This report describes in detail how the researchers turned findings into recommendations, and how the various stages of stakeholder consultation influenced different elements of the project. It includes a step-by-step illustration of the stakeholder engagement process, which is also available a separate graphic

Baseline report: understanding the links and interactions between low sanitation and health insurance in India

This document reports on the baseline data collection for the project titled “Understanding the Links and Interactions between Low Sanitation and Health Insurance in India”, funded through the Strategic Impact Evaluation Fund (SIEF). The overall purpose of this project is to shed light on (i) innovative ways of increasing the uptake and usage of safe sanitation practices and (ii) provide evidence on the links and interactions between improved sanitation and health insurance. It does so by studying two distinct but topically-linked projects: The smaller of these two projects is designed to explore the potential of providing primary community health insurance for free to communities that reduced open defecation conditional on sustaining this tendency. This component of the project is still in the development phase and will hence not be covered in this report. The second project, which includes a full randomised controlled trial impact evaluation, analyses two variants of an intervention, which in achieving sustainable improvements in household and community sanitation, aims to improve the health and reduce health expenditures of the poor in rural India - potentially reflected in lower health care claims volumes. This report discusses the activities and findings of the baseline data collection for this RCT component. The two overarching aims are (1) to provide an interesting snapshot of our study population, serving as a useful tool to understand the context in which the intervention is taking place, and (2) to formally test whether we see any systematic differences between the treatment and control group prior to the intervention starting. We see this document as an important reference for processes followed, decisions made and their rationale, and related outcomes for everything relevant to the Impact Evaluation (IE) design and hope that it will serve as a useful guide for anyone interested in using the project's data or understanding the analysis we will undertake going forward

Designing development interventions: The application of service design and discrete choice experiments in complex settings

The persistence of problems such as endemic poverty, rising inequalities, climate change and biodiversity loss demands us to find solutions which are embedded in a highly complex web of interacting social, technological, and ecological processes. Service design (SD), an approach to directly involve citizens in the development and improvement of services and systems, shows promise as a tool to support the design of interventions to address complex development challenges in the Global South. In this paper we describe how service design was used alongside discrete choice experiments (DCEs) to inform the design of a Weather Index Insurance product for small holder farmers in Uganda. As part of the service design process, we used archetypes to capture and articulate the multiple vulnerabilities of farmers and quickly test prototype insurance packages to identify important design features. DCEs tested promising design features in a manner that complemented as well as triangulated the service design phase. The results of both phases were used to inform the design of a WII product that has been taken up by major insurance providers in Uganda. The approach complements and builds on qualitative work typically done to inform DCEs by opening up space for research participants to question core assumptions, and by involving respondents directly in the process of designing a future service

Neotropical freshwater fisheries : A dataset of occurrence and abundance of freshwater fishes in the Neotropics

The Neotropical region hosts 4225 freshwater fish species, ranking first among the world's most diverse regions for freshwater fishes. Our NEOTROPICAL FRESHWATER FISHES data set is the first to produce a large-scale Neotropical freshwater fish inventory, covering the entire Neotropical region from Mexico and the Caribbean in the north to the southern limits in Argentina, Paraguay, Chile, and Uruguay. We compiled 185,787 distribution records, with unique georeferenced coordinates, for the 4225 species, represented by occurrence and abundance data. The number of species for the most numerous orders are as follows: Characiformes (1289), Siluriformes (1384), Cichliformes (354), Cyprinodontiformes (245), and Gymnotiformes (135). The most recorded species was the characid Astyanax fasciatus (4696 records). We registered 116,802 distribution records for native species, compared to 1802 distribution records for nonnative species. The main aim of the NEOTROPICAL FRESHWATER FISHES data set was to make these occurrence and abundance data accessible for international researchers to develop ecological and macroecological studies, from local to regional scales, with focal fish species, families, or orders. We anticipate that the NEOTROPICAL FRESHWATER FISHES data set will be valuable for studies on a wide range of ecological processes, such as trophic cascades, fishery pressure, the effects of habitat loss and fragmentation, and the impacts of species invasion and climate change. There are no copyright restrictions on the data, and please cite this data paper when using the data in publications