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- W2044148859 abstract "We develop numerically stable and accurate stochastic simulation approaches for solving dynamic economic models. First, instead of standard least-squares approximation methods, we examine a variety of alternatives, including least-squares methods using singular value decomposition and Tikhonov regularization, least-absolute deviations methods, and principal component regression method, all of which are numerically stable and can handle ill-conditioned problems. Second, instead of conventional Monte Carlo integration, we use accurate quadrature and monomial integration. We test our generalized stochastic simulation algorithm (GSSA) in three applications: the standard representative–agent neoclassical growth model, a model with rare disasters, and a multicountry model with hundreds of state variables. GSSA is simple to program, and MATLAB codes are provided." @default.
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- W2044148859 date "2011-07-01" @default.
- W2044148859 modified "2023-10-18" @default.
- W2044148859 title "Numerically stable and accurate stochastic simulation approaches for solving dynamic economic models" @default.
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- W2044148859 doi "https://doi.org/10.3982/qe14" @default.
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