<mark>to drought conditions is important in order to facilitate the evaluation of the sovereign level food security model in terms of its bias (over‐ or under‐prediction) and basis risk in estimating the number of food insecure people (Clarke and Hill 2013).</mark> Other considerations that need to be made from an operational perspective are that the model be kept as simple and transparent as possible. As discussed earlier in the context of food security assessments, complex models are also difficult to calibrate either because of the large number of parameters that can be tuned and/or because of the complex nature of their interactions.

Still another consideration is that the model needs to be consistent, meaning that once the parameters are set the model is locked and no further _ad hoc_ changes are allowed.

Lastly, domestic technical capacity needs to be built in the developing countries for which the models are built not just to run the models but to enable countries to carry on processing the data and improving the model on their own. In this respect the approach taken by ARC to allow domestic experts in their respective countries to customize the model is promising.

# <u>Conclusion</u>

The availability of RS weather data, drought indices and crop models for the major staple crops have made it possible to develop catastrophe crop models. While there are a number of issues that still need to be addressed on the technology side of hazard and crop modeling, mapping of grid to administrative boundaries, etc. the major issue lies in the availability of data on the cultivar, soil type, crop coefficients, etc. at the grid level. The output of catastrophe crop models in the form of a probabilistic distribution of the production shock can be input to a food security vulnerability model to assess the number of food insecure people. Currently, the food security vulnerability model is the weakest link in estimating the number of food insecure people. There is need for more detailed analysis at the household level in actual drought conditions that could lead to simple but robust assessments of food insecurity. The situation in food security modeling today is not very much unlike the early days of catastrophe property modeling when simple, transparent, easy to calibrate and validate methodologies were used, which in the course of time became more analytical and more robust.

# <u>Acknowledgements</u>

The authors would like to acknowledge the very helpful discussions with Dr. Joanna Syroka, Project Team Leader, African Risk Capacity, Dr. Auguste Boissonnade, Chief Technology Officer, Asia Risk Centre and Dr. Daniel Clarke, Senior Disaster Risk Financing Specialist, World Bank.

# <u>References</u>

Adamopoulos, T. and Restuccia,D. 2011. _The Size Distribution of Farms and International Productivity Differences_ , Department of Economics, University of Toronto, Working Paper 441.

ARC 2012. Guidelines for Drafting Plans for the Use of ARC Payouts Barrett, C. B., Binder, A., Gaus, A., Lentz, E.C., Mathys, C., Steets, J., Upton, J. and Villa, K. 2011 Uniting in Food Assistance, GPPi and Cornell University Butler, D. 2013. _Crowdsourcing goes mainstream in typhoon response_ , Nature, 20 Nov 2013 21