This article describes a new approximation method for dynamic stochastic general equilibrium (DSGE) models. The method … allows nonlinear models to be estimated efficiently and relatively quickly with the fully-adapted particle filter. The … article demonstrates the method by estimating, on US data, a nonlinear New Keynesian model with a zero lower bound on the …

volatility to evaluate the sign and size of uncertainty shocks. The authors use a nonlinear DSGE model to gain deeper insights … monetary policy uncertainty into South Africa using a stochastic volatility model and a nonlinear DSGE model. The results … a contemporaneous decrease. The DSGE model shows that the size of the uncertainty shock matters – high uncertainty can …

(DSGE) models with rare disasters along the lines of those proposed by Rietz (1988), Barro (2006), Gabaix (2012), and Gourio … (2012). DSGE models with rare disasters require solution methods that can handle the large nonlinearities triggered by low …-varying disaster risk with perturbation, Taylor projection, and Smolyak collocation. Our main finding is that Taylor projection …

(DSGE) models with rare disasters along the lines of those proposed by Rietz (1988), Barro (2006), Gabaix (2012), and Gourio … (2012). DSGE models with rare disasters require solution methods that can handle the large nonlinearities triggered by low …‐varying disaster risk with perturbation, Taylor projection, and Smolyak collocation. Our main finding is that Taylor projection …

(DSGE) models with recursive preferences such as those in Epstein and Zin (1989 and 1991) and stochastic volatility. Models … using four different approaches: second- and third-order perturbation, Chebyshev polynomials, and value function iteration … while being several orders of magnitude faster to run. Therefore, we conclude that perturbation methods are an attractive …

techniques that increase the accuracy of perturbation methods: a change of variables and a hybrid of local and global solutions …

(DSGE) models with recursive preferences such as those in Epstein and Zin (1989 and 1991). Models with these preferences …-order perturbation, Chebyshev polynomials, and value function iteration. We document the performance of the methods in terms of computing … time, implementation complexity, and accuracy. Our main finding is that a third-order perturbation is competitive in terms …