DP11032 Solution and Estimation Methods for DSGE Models
|Author(s):||Jesús Fernández-Villaverde, Juan Francisco Rubio-Ramírez, Frank Schorfheide|
|Publication Date:||December 2015|
|Keyword(s):||approximation error analysis, Bayesian inference, DSGE model, frequentist inference, GMM estimation, impulse response function matching, likelihood-based inference, Metropolis-Hastings algorithm, minimum distance estimation, particle filter, perturbation methods, projection methods, sequential Monte Carlo|
|JEL(s):||C11, C13, C32, C52, C61, C63, E32, E52|
|Programme Areas:||Monetary Economics and Fluctuations|
|Link to this Page:||cepr.org/active/publications/discussion_papers/dp.php?dpno=11032|
This paper provides an overview of solution and estimation techniques for dynamic stochastic general equilibrium (DSGE) models. We cover the foundations of numerical approximation techniques as well as statistical inference and survey the latest developments in the field.