Abstract
Efficiency in water allocation for agricultural uses in evaluated here through quadratic programming (QP) models, which explicitly incorporate risk aversion due to yield and price fluctuations and endogenous demand functions econometrically estimated. These models, when empirically applied to Santa Maria Valley in Santa Barbara County over the period 1959–80 generate optimal solutions, through which one can evaluate the shadow price elasticity of demand and the impact of prices on optimum supply. These evaluations show the QP model solutions to be more robust and reliable than the linear programming solutions; hence, their shadow prices may be used in securing efficiency in the allocation of agricultural water.
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