A Decision-Analytic Framework to explore the water-energy-food nexus in complex and transboundary water resources systems, with Climate Change Uncertainty

In this paper we develop and apply a stochastic multistage dynamic cooperative game for managing transboundary water resources, within the water-food-energy nexus framework, under climate uncertainty. The mathematical model is solved for the non-cooperative and cooperative (Stackelberg 'leader-follower') cases and is applied to the Omo-Turkana River Basin in Africa. The empirical application of the model calls for sector-specific production function estimations, for which we employ nonparametric treatment of the production functions a la Gandhi, Navarro, and Rivers (2017), while we extend it to allow for technical inefficiency in production and autocorrelated TFP. Bayesian analysis is performed using a Sequential Monte Carlo / Particle-Filtering approach. We find that the cooperative solution is the optimal pathway not only for both riparian countries, but for the sustainable use of the basin as well, whereas in extreme Climate Change circumstances it remains the welfare maximizing option. We argue that the detail and sophistication of both the mathematical and econometric models are needed for robust policy recommendations towards sustainable management of transboundary resources.