A Higher-Order Taylor Expansion Approach to Simulation of Stochastic Forward-Looking Models with an Application to a Nonlinear Phillips Curve Model

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Accuracy of stochastic perturbation methods: The case of asset pricing models (2001, methodology): “There now exists a wide range of methods to approximate the agent's decision rules: LQ approximation (Kydland and Prescott, 1982; Cooley and Prescott, 1995), parameterized expectation algorithm (Marcet, 1988), Gaussian quadrature (Tauchen and Hussey, 1991), minimum weighted residual methods (Judd, 1”
Dynare add-on for "Solving DSGE Models with a Nonlinear Moving Average" (2013, methodology): “…Judd (1997), Judd and Guu (1997), and Judd (1998, ch. 13) has thus far operated solely with state-space methods, see Collard and Juillard (2001b), Collard and Juillard (2001a), Jin and Judd (2002), Schmitt-Grohé and Uribe (2004), Anderson, Levin, and Swanson (2006), Lombardo and Sutherland…”