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The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. ABSTRACT We develop a projection method that can solve dynamic economic models with a large number of state variables. A distinctive feature of our method is that it operates on the ergodic set realized in equilibrium: we(More)
This paper studies a complete-market version of the neoclassical growth model, where agents face idiosyncratic shocks to earnings. We show that if agents possess identical preferences of either the CRRA or the addilog type, then the heterogeneous-agent economy behaves as if there was a representative consumer who faces three kinds of shocks, to preferences,(More)
JEL classification: C6 C63 D52 Keywords: Dynamic stochastic models Heterogeneous agents Aggregate uncertainty Euler-equation methods Simulations Numerical solutions a b s t r a c t This paper studies the properties of the solution to the heterogeneous agents model in Den Haan et al. [2009. Computational suite of models with heterogeneous agents: incomplete(More)
We develop numerically stable stochastic simulation approaches for solving dynamic economic models. We rely on standard simulation procedures to simultaneously compute an ergodic distribution of state variables, its support and the associated decision rules. We differ from existing methods, however, in how we use simulation data to approximate decision(More)
This is a substantially revised version of the NBER working paper 15965 entitled "A Cluster-Grid Projection Method: Solving Problems with High Dimensionality. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment(More)
Does a heterogeneous agents version of a neoclassical model with labor}leisure choice replicate the distributions of consumption and working hours observed in the cross-sectional data? Does incorporating heterogeneity enhance the aggregate performance of the representative agent model? We address these questions in a complete market model economy with two(More)
We apply the stochastic simulation algorithm, described in Judd, Maliar and Maliar (2009), and the projection cluster-grid algorithm, developed in Judd, Maliar and Maliar (2010a), to solving a collection of multi-country models. Four techniques help us reduce the cost in high-dimensional problems: an endogenous grid enclosing the ergodic set, linear(More)
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 regulariza-tion, least-absolute deviations methods, and(More)