Computing solutions to moral-hazard programs using the Dantzig-Wolfe decomposition algorithm

Abstract Linear programming is an important method for computing solutions to private-information programs. The method is applicable for arbitrary specifications of preferences and technology. Unfortunately, as the cardinality of underlying sets increases, the programs quickly become too large to compute. This paper demonstrates that moral-hazard programs have a structure that allows them to be computed using the Dantzig–Wolfe decomposition algorithm. This algorithm breaks the linear program into subprograms, greatly increasing the size of programs that may be practically computed. Two examples are computed. The role of action lotteries is discussed.

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