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Computing moral-hazard problems using the Dantzig-Wolfe decomposition algorithm

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  • Edward Simpson Prescott

Abstract

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

Suggested Citation

  • Edward Simpson Prescott, 1998. "Computing moral-hazard problems using the Dantzig-Wolfe decomposition algorithm," Working Paper 98-06, Federal Reserve Bank of Richmond.
  • Handle: RePEc:fip:fedrwp:98-06
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    Citations

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    Cited by:

    1. Jorge Aseff & Manuel Santos, 2005. "Stock options and managerial optimal contracts," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 26(4), pages 813-837, November.
    2. Alexander Karaivanov, 2002. "Computing Moral Hazard Programs With Lotteries Using Matlab," Computational Economics 0201001, EconWPA.
    3. Andreas Lehnert, 1998. "Asset pooling, credit rationing, and growth," Finance and Economics Discussion Series 1998-52, Board of Governors of the Federal Reserve System (U.S.).
    4. Edward Simpson Prescott, 1999. "A primer on moral-hazard models," Economic Quarterly, Federal Reserve Bank of Richmond, issue Win, pages 47-78.

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