Solving the incomplete markets model with aggregate uncertainty using parameterized cross-sectional distributions
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- handle: 10670/1.8522oh
- hal: hal-02662044
- doi: 10.1016/j.jedc.2009.03.010
- PRODINRA: 31290
- SCIENCESPO: 2441/72lkhuq5cm8hqrn860asm92bvs
- WOS: 000272635200007
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PROJECTION METHODS Numerical Solutions Projection Methods Simulations NUMERICAL SOLUTIONS SIMULATIONS C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C63 - Computational Techniques • Simulation Modeling D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D52 - Incomplete MarketsCiter ce document
Yann Algan et al., « Solving the incomplete markets model with aggregate uncertainty using parameterized cross-sectional distributions », Archive ouverte de Sciences Po (SPIRE), ID : 10.1016/j.jedc.2009.03.010
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This note describes how the incomplete markets model with aggregate uncertainty in Den Haan et al. [Comparison of solutions to the incomplete markets model with aggregate uncertainty. Journal of Economic Dynamics and Control, this issue] is solved using standard quadrature and projection methods. This is made possible by linking the aggregate state variables to a parameterized density that describes the cross-sectional distribution. A simulation procedure is used to find the best shape of the density within the class of approximating densities considered. This note compares several simulation procedures in which there is—as in the model—no cross-sectional sampling variation.