Solving the Stochastic Growth Model by Backsolving With a Particular Nonlinear Form for the Decision Rule
介绍一种反向求解方法，通过假设欧拉方程扰动的分布来生成随机均衡模型中外生冲击的模拟值，并将近似误差转移到冲击分布而非欧拉方程中，应用于单部门新古典增长模型。
Backsolving is a class of methods that generate simulated values for exogenous forcing processes in a stochastic equilibrium model from specified assumed distributions for Euler-equation disturbances. It can be thought of as a way to force the approximation error generated by inexact choice of decision rule or boundary condition into distortions of the distribution of the exogenous shocks in the simulations rather than into violations of the Euler equations as with standard approaches. Here it is applied to a one-sector neoclassical growth model with decision rule generated from a linear-quadratic approximation.