As envisaged in the Sustainable Development Goals, eradicating poverty by 2030 is among the most important steps to achieve a better and more sustainable future. A key contribution to reach this target is to ensure that vulnerable households are effectively protected against weather-related extreme events and other economic, social and ecological shocks and disasters. Insurance products specifically designed for the needs of low-income households in developing countries are seen as an effective instrument to encompass also the poor with an affordable risk-coping mechanism and are thus highly promoted and supported by governments in recent years. However, apart from direct positive effects, the introduction of formal insurance may have unintended side effects. In particular, it might affect traditional risk-sharing arrangements where income losses are covered by an exchange of money, labour and in-kind goods between neighbours, relatives or friends. A weakening of informal safety nets may increase social inequality if poor households cannot afford formal insurance. In order to design insurance products in a sustainable way, sound understanding of their interplay with risk-sharing networks is urgently needed. Socio-environmental modelling is a suitable approach to address the complexity of this challenge. In the first part of this thesis, an agent-based model is developed to investigate the effects of formal insurance and informal risk-sharing on the resilience of smallholders. To lay the conceptual foundation for this approach, a literature review is presented which provides an overview of how to couple agent-based modelling with social network analysis. In two subsequent modelling studies, it is analysed (i) how the introduction of insurance influences the overall welfare in a population and (ii) what determines the resilience of the poorest to shocks when income is heterogeneously distributed and not all households can afford formal insurance. The simulation results underline the importance of designing insurance policies in close alignment with established risk-coping arrangements to ensure sustainability while striving to eradicate poverty. It is shown that introducing formal insurance can have negative side effects when insured households have fewer resources to share with their uninsured peers after paying the insurance premium or when they reduce their solidarity. However, especially when many households are simultaneously affected by a shock, e.g. by droughts or floods, formal insurance is a valuable addition to informal risk-sharing. By applying a regression analysis to simulation results for an empirical network from the Philippines, it is furthermore inferred that network characteristics must be considered in addition to individual household properties to identify the most vulnerable households that neither have access to formal insurance nor are adequately protected through informal risk-sharing. In the second part of this thesis, a broader perspective is taken on the use of models in socio-environmental systems. First, it is envisioned how models in combination with empirical studies could improve insurance design under climate change. Second, requirements for making socio-environmental modelling more useful to support policy and management and scientific results more influential on policy-making are synthesised. Overall, this thesis offers new insights into the interplay of formal and informal risk-coping instruments that complement existing empirical research and underlines the potential of socio-environmental modelling to address sustainability and development challenges.
| Identifer | oai:union.ndltd.org:uni-osnabrueck.de/oai:osnadocs.ub.uni-osnabrueck.de:ds-202112205724 |
| Date | 20 December 2021 |
| Creators | Will, Meike |
| Contributors | Prof. Dr. Karin Frank, Prof. Dr. Tatiana Filatova, Prof. Dr. Jacopo A. Baggio |
| Source Sets | Universität Osnabrück |
| Language | English |
| Detected Language | English |
| Type | doc-type:doctoralThesis |
| Format | application/pdf, application/zip |
| Rights | Attribution 3.0 Germany, http://creativecommons.org/licenses/by/3.0/de/ |
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