Using three examples consisting of an artifcial state-space model, the Smets and Wouters (2007) model, and Schmitt-Grohé and Uribe’s (2012) news shock model the authors show that the SMC algorithm is better suited for multi-modal and irregular posterior distributions than the widely-used random walk Metropolis-Hastings algorithm. Unlike standard Markov chain Monte Carlo (MCMC) techniques, the SMC algorithm is well suited for parallel computing.