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Abstract

This paper shows how to solve dynamic agency models by extending recursive Lagrangean techniques a la Marcet and Marimon 2009 to problems with hidden actions. The method has many advantages with respect to promised utilities approach Abreu, Pearce and Stacchetti 1990: it is a significant improvement in terms of simplicity, tractability and computational speed. Solutions can be easily computed for hidden actions models with several endogenous state variables and several agents, while the promised utilities approach becomes extremely difficult and computationally intensive even with just one state variable or two agents. Several numerical examples illustrate how this methodology outperforms the standard approach.



Item Type: MPRA Paper -

Original Title: Repeated moral hazard and recursive Lagrangeans-

Language: English-

Keywords: repeated moral hazard; recursive Lagrangean; collocation method-

Subjects: D - Microeconomics > D8 - Information, Knowledge, and Uncertainty > D86 - Economics of Contract: TheoryC - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling > C63 - Computational Techniques ; Simulation ModelingD - Microeconomics > D8 - Information, Knowledge, and Uncertainty > D82 - Asymmetric and Private Information ; Mechanism DesignC - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling > C61 - Optimization Techniques ; Programming Models ; Dynamic Analysis-





Autor: Mele, Antonio

Fuente: https://mpra.ub.uni-muenchen.de/21741/







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