prof. dr. Maarten van Aalst, A second-supervisor: still to be identified, Ceciclia Costella (advisor; PhD resseacher at ITC\ Senior Social Protection Advisor at the Red Cross Red Crescent Climate Centre)
This research aims to explore to what extent the use of climate risk information can help improve the ability of social assistance programs to reach those who are most vulnerable to climate risk, especially the impacts of extreme events. Social protection (SP) programs (cash transfers, safety nets, and other social policies) are increasingly considered as suitable policy instruments to reach and support those most vulnerable to climate risks in developing countries. Some argue that SP programs are able to protect and support people who are vulnerable to climate risks by being targeted to the poorest and those who are in categories that are socially vulnerable (usually the elderly, people with disabilities, etc.). Others have argued that social protection needs to incorporate specific climate vulnerability indicators in order to reach them. This research aims to compare the targeting efficiency of social protection programs through a comparison of SP targeting methods with and without climate vulnerability indicators. The purpose is to explore the ability of a climate-cognizant targeting mechanism to select the “right people” to receive a particular benefit in advance or after a shock (e.g. selecting those most likely to suffer the highest relative loss, or another measure of shock impact).
This research plans to compare a regular social protection (SP) targeting method (often income- or categorically-based) with a method that integrates natural hazard risk information (“climate-informed” method). The climate-informed method would be based on risk index that is based in a a holistic risk analysis that considers physical and social aspects of vulnerability to climate.
Since, to our knowledge no SP program uses such index, the climate-vulnerability targeting method could be modelled upon more basic indices of climate risk.
The research will then test the efficiency of the regular SP targeting and the climate-informed method on a dataset representative of the intended population to which the method will be applied to (for instance, those in the World Bank’s Living Standards Measurement Study surveys, or those in baseline surveys for some social protection programs, such as the Hunger Safety Net Programme in Kenya).
Countries pre-identified with availability of data and possible initial connections that would allow conducting research are Malawi, Kenya, Uganda, Niger, and Dominican Republic.