
In this paper, I evaluate the performance of two recently proposed approaches to solving and estimating structural models: The Endogenous Grid Method (EGM) and Mathematical Programming with Equilibrium Constraints (MPEC). Monte Carlo simulations confirm that both the EGM and MPEC have advantages relative to standard methods. The EGM proved particularly robust, fast and straightforward to implement. Approaches trying to avoid solving the model numerically, therefore, seem to be dominated by these approaches.
Endogenous Grid Method (EGM), /dk/atira/pure/core/keywords/FacultyOfSocialSciences, Continuous choice, /dk/atira/pure/core/keywords/FacultyOfSocialSciences; name=Faculty of Social Sciences, Mathematical Programming with Equilibrium Constraints (MPEC), Structural estimation, Faculty of Social Sciences
Endogenous Grid Method (EGM), /dk/atira/pure/core/keywords/FacultyOfSocialSciences, Continuous choice, /dk/atira/pure/core/keywords/FacultyOfSocialSciences; name=Faculty of Social Sciences, Mathematical Programming with Equilibrium Constraints (MPEC), Structural estimation, Faculty of Social Sciences
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