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We develop a sequential Monte Carlo (SMC) algorithm for estimating Bayesian dynamic stochastic general equilibrium (DSGE) models, wherein a particle approximation to the posterior is built iteratively through tempering the likelihood. Using three examples consisting of an artificial state-space...
Persistent link: https://www.econbiz.de/10013097300
state-observation sampling (SOS) filter, for general state-space models with intractable observation densities. Second, we …
Persistent link: https://www.econbiz.de/10013093423
The normalized importance sampling estimator allows the target density f to be known only up to a multiplicative … importance sampling estimator in terms of mean square error …
Persistent link: https://www.econbiz.de/10013073823
We develop a sequential Monte Carlo (SMC) algorithm for estimating Bayesian dynamic stochastic general equilibrium (DSGE) models, wherein a particle approximation to the posterior is built iteratively through tempering the likelihood. Using three examples -- an artificial state-space model, the...
Persistent link: https://www.econbiz.de/10013074664
Many statistical and econometric learning methods rely on Bayesian ideas, often applied or reinterpreted in a frequentist setting. Two leading examples are shrinkage estimators and model averaging estimators, such as weighted-average least squares (WALS). In many instances, the accuracy of these...
Persistent link: https://www.econbiz.de/10012839923
This paper investigates the finite sample properties of the widely-used Gibbons, Ross, Shanken (1989) (GRS) test in the presence of both conditional correlation and conditional heteroskedasticity. It finds that the GRS test exhibits serious size distortions resulting in potentially misleading...
Persistent link: https://www.econbiz.de/10012943966
Monte Carlo (MC) approximation of the standard Gibbs procedure which uses sequential MC (SMC) importance sampling inside the … generic and easily implementable SMC approach known as Particle Efficient Importance Sampling (PEIS). By using SMC importance … sampling densities which are approximately fully globally adapted to the targeted density of the states, PEIS can substantially …
Persistent link: https://www.econbiz.de/10012970355
The aim of these notes is to revisit sequential Monte Carlo (SMC) sampling. SMC sampling is a powerful simulation tool …
Persistent link: https://www.econbiz.de/10012993836
the finite population mean under a two-phase sampling system. The Bias and Mean Square Error (MSE) of the proposed …
Persistent link: https://www.econbiz.de/10013272887
Vector autoregressions with Markov-switching parameters (MS-VARs) offer dramatically better data fit than their constant-parameter predecessors. However, computational complications, as well as negative results about the importance of switching in parameters other than shock variances, have...
Persistent link: https://www.econbiz.de/10013031756