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Solving nonlinear dynamic stochastic models: An algorithm computing value function by simulations
Nonlinear stochastic models Value function Parameterized expectations Monte Carlo simulations Numerical solutions
2015/7/21
This paper presents an algorithm for solving nonlinear dynamic stochastic models that computes value function by simulations. We argue that the proposed algorithm can be a useful alternative to the ex...
Envelope condition method versus endogenous grid method for solving dynamic programming problems
Hoover Institution, Stanford University, USA University of Alicante, Spain
2015/7/21
We introduce an envelope condition method (ECM) for solving dynamic programming problems. The ECM method is simple to implement, dominates conventional value function iteration and is comparable in ac...
Smolyak method for solving dynamic economic models: Lagrange interpolation, anisotropic grid and adaptive domain
Smolyak method Sparse grid Adaptive domain Projection Anisotropic grid High-dimensional problem
2015/7/21
We show how to enhance the performance of a Smolyak method for solving dynamic economic models. First, we propose a more efficient implementation of the Smolyak
method for interpolation, namely, we s...
Consistency properties of a simulation-based estimator for dynamic processes
Consistency properties simulation-based estimator dynamic processes
2010/10/18
This paper considers a simulation-based estimator for a general class of Markovian processes and explores some strong consistency properties of the estimator. The estimation problem is defined over a ...