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This note presents the R package bayesGARCH (Ardia, 2007) which provides functions for the Bayesian estimation of the … parsimonious and effective GARCH(1,1) model with Student-t innovations. The estimation procedure is fully automatic and thus avoids …
Persistent link: https://www.econbiz.de/10011380176
We propose a nonparametric Bayesian approach for conducting inference on probabilistic surveys. We use this approach to …
Persistent link: https://www.econbiz.de/10014080529
dependent variables. With so many parameters to estimate, Bayesian prior shrinkage is vital in achieving reasonable results … overcome the computational hurdle and allow for Bayesian inference in large VARs with a range of hierarchical shrinkage priors …
Persistent link: https://www.econbiz.de/10014108644
form is a tractable known model for which I provide the first algorithm for Bayesian estimation of all free parameters. I …
Persistent link: https://www.econbiz.de/10014111397
In this paper, we provide evidence that fat tails and stochastic volatility can be important in improving in-sample fit and out-of-sample forecasting performance. Specifically, we construct a VAR model where the orthogonalised shocks feature Student's t distribution and time-varying variance. We...
Persistent link: https://www.econbiz.de/10013021982
This chapter provides an overview of solution and estimation techniques for dynamic stochastic general equilibrium models. We cover the foundations of numerical approximation techniques as well as statistical inference and survey the latest developments in the field.
Persistent link: https://www.econbiz.de/10014024288
using Markov chain Monte Carlo in O(Mn) operations, where n is the sample size and M and is the number of iterations. We …A Bayesian analysis is presented of a time series which is the sum of a stationary component with a smooth spectral … Bayesian framework and estimated simultaneously. A Bayesian test to detect the presence of deterministic components in the data …
Persistent link: https://www.econbiz.de/10014029563
The paper provides a novel Bayesian methodological framework to estimate structural VAR (SVAR) models with recursive …
Persistent link: https://www.econbiz.de/10013097952
This paper proposes full-Bayes priors for time-varying parameter vector autoregressions (TVP-VARs) which are more robust and objective than existing choices proposed in the literature. We formulate the priors in a way that they allow for straightforward posterior computation, they require...
Persistent link: https://www.econbiz.de/10013059299
We present a new method for estimating Bayesian vector auto-regression (VAR) models using priors from a dynamic … maximize the marginal likelihood of the Bayesian VAR provides a method for isolating subsets of DSGE parameter priors that are … variance of structural shocks using a Monte Carlo experiment. We also demonstrate how posterior estimates of the DSGE parameter …
Persistent link: https://www.econbiz.de/10012925686