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 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 …

(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 …

(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 …