Estimating dynamic equilibrium economies: linear versus nonlinear likelihood
动态均衡经济的估计：线性与非线性似然比较
Abstract This paper compares two methods for undertaking likelihood‐based inference in dynamic equilibrium economies: a sequential Monte Carlo filter and the Kalman filter. The sequential Monte Carlo filter exploits the nonlinear structure of the economy and evaluates the likelihood function of the model by simulation methods. The Kalman filter estimates a linearization of the economy around the steady state. We report two main results. First, both for simulated and for real…