SEEMI (finished)

Duration: 01.03.2017 - 31.08.2020

Insurance products specially designed for the needs of low-income people in developing countries are seen as a promising tool for economic development, and are therefore strongly promoted and supported by governments. These so-called microinsurance products cover specific risks like health risks or climate-related agricultural risks. They contribute effectively to improving resilience, e.g. when an entire community is affected and informal safety nets, i.e. the traditional arrangements of households to share risk, can no longer absorb the losses.  Assessment studies of such policies show, however, that apart from direct positive effects they may have unintended side effects.  Within the SEEMI research project we contributed to a much-needed enhanced understanding of the effects of microinsurance on social-ecological systems.

Specifically, we will addressed the following research questions:

1. Under which conditions will microinsurance crowd out informal safety nets? Could this decrease communal welfare and exacerbate social inequalities?
2. Under which circumstances can microinsurance act as a complement to informal safety nets?

To answer these questions, we combined the approach of agent-based modelling with social network analysis to develop a stylized dynamic simulation model. The innovation of this approach is that it simultaneously takes into consideration feedbacks in the social-ecological system, interactions between actors, and changes in social structures. Our model-based analysis was guided by two case studies: (a) drought insurance in Kenya and Ethiopia and (b) health insurance in Cambodia.

Thanks to our systematic approach of gradually increasing complexity, we achieved contribution to knowledge on two levels. First, we offered process-based explanations of empirically observable patterns from the case studies; and second, we advanced a thorough understanding of the effects of microinsurance at the systems level – particularly regarding the relevance of social-ecological feedbacks.

The project was funded by the German Research Foundation (DFG).