Financing agricultural drought risk through ex-ante cash transfers

Gabriela Guimarães Nobre, Frank Davenport, Konstantinos Bischiniotis, Ted Veldkamp, Brenden Jongman, Christopher C. Funk, Gregory Husak, Philip J. Ward, Jeroen C.J.H. Aerts

Research output: Contribution to JournalArticleAcademicpeer-review


Despite advances in drought early warning systems, forecast information is rarely used for triggering and financing early actions, such as cash transfer. Scaling up cash transfer pay-outs, and overcoming the barriers to actions based on forecasts, requires an understanding of costs resulting from False Alarms, and the potential benefits associated with appropriate early interventions. On this study, we evaluate the potential cost-effectiveness of cash transfer responses, comparing the relative costs of ex-ante cash transfers during the maize growing season to ex-post cash transfers after harvesting in Kenya. For that, we developed a forecast model using Fast-and Frugal Trees that unravels early warning relationships between climate variability, vegetation coverage, and maize yields at multiple lead times. Results indicate that our models correctly forecast low maize yield events 85% of the time across the districts studied, some already six months before harvesting. The models' performance improves towards the end of the growing season driven by a decrease of 29% in the probability of False Alarms. Overall, we show that timely cash transfers ex-ante to a disaster can often be more cost-effective than investing in ex-post expenditures. Our findings suggest that early response can yield significant cost savings, and can potentially increase the effectiveness of existing cash transfer systems.
Original languageEnglish
Pages (from-to)523-535
Number of pages13
JournalScience of the Total Environment
Publication statusPublished - 25 Feb 2019


The research leading to this article is funded by the Horizon 2020 Framework programme through the project IMPREX (grant agreement no. 641811 ). J.C.J.H. and P.J.W. received additional support from the Netherlands Organisation for Scientific Research (NWO) in the form of VICI grant 453.140.006 and VIDI grant 016.161.324 respectively.

FundersFunder number
Horizon 2020 Framework Programme641811
Nederlandse Organisatie voor Wetenschappelijk Onderzoek453.140.006, 016.161.324


    • Cash transfer
    • Disaster risk financing
    • Drought
    • Food security
    • Forecasting
    • Machine learning


    Dive into the research topics of 'Financing agricultural drought risk through ex-ante cash transfers'. Together they form a unique fingerprint.

    Cite this