Recursive Contracts, Lotteries and Weakly Concave Pareto Sets

Harold Cole and Felix Kubler

PIER Working Paper Archive from Penn Institute for Economic Research, Department of Economics, University of Pennsylvania

Abstract: Marcet and Marimon (1994, revised 1998) developed a recursive saddle point method which can be used to solve dynamic contracting problems that include participation, enforcement and incentive constraints. Their method uses a recursive multiplier to capture implicit prior promises to the agent(s) that were made in order to satisfy earlier instances of these constraints. As a result, their method relies on the invertibility of the derivative of the Pareto frontier and cannot be applied to problems for which this frontier is not strictly concave. In this paper we show how one can extend their method to a weakly concave Pareto frontier by expanding the state space to include the realizations of an end of period lottery over the extreme points of a .at region of the Pareto frontier. With this expansion the basic insight of Marcet and Marimon goes through .one can make the problem recursive in the Lagrangian multiplier which yields significant computational advantages over the conventional approach of using utility as the state variable. The case of a weakly concave Pareto frontier arises naturally in applications where the principal’s choice set is not convex but where randomization is possible.

Keywords: Recursive Contracting; Recursive Multipliers; Lotteries (search for similar items in EconPapers)
JEL-codes: C61 C63 (search for similar items in EconPapers)
Pages: 31 pages
Date: 2010-12-10
New Economics Papers: this item is included in nep-dge
References: View complete reference list from CitEc
Citations: View citations in EconPapers (9)

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Related works:
Journal Article: Recursive Contracts, Lotteries and Weakly Concave Pareto Sets (2012)
Working Paper: Recursive Contracts, Lotteries and Weakly Concave Pareto Sets (2011)
Working Paper: Recursive Contracts, Lotteries and Weakly Concave Pareto Sets (2011)
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