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On the practice of Bayesian inference in basic economic time series models using Gibbs sampling

Pooter, Michiel de; Segers, Rene; Dijk, Herman K. van - 2006

Several lessons learned from a Bayesian analysis of basic economic time series models by means of the Gibbs sampling …

Persistent link: https://www.econbiz.de/10011349180

Marginal Likelihood Estimation with the Cross-Entropy Method

Chan, Joshua; Eisenstat, Eric - 2012

We consider an adaptive importance sampling approach to estimating the marginal likelihood, a quantity that is … importance sampling approach is that random samples can be obtained from some convenient density with little additional costs. As … method is grounded in information theory, and therefore, is in a well-defined sense optimal. We demonstrate the utility of …

Persistent link: https://www.econbiz.de/10014169831

Joint Bayesian Analysis of Parameters and States in Nonlinear, Non-Gaussian State Space Models

Barra, Istvan - 2016

these proposal densities are used in an independent Metropolis-Hastings algorithm or in importance sampling. Our method …

Persistent link: https://www.econbiz.de/10013005987

An alternative Bayesian approach to structural breaks in time series models

Hauwe, Sjoerd van den; Paap, Richard; Dijk, Dick van - 2011

We propose a new approach to deal with structural breaks in time series models. The key contribution is an alternative dynamic stochastic specification for the model parameters which describes potential breaks. After a break new parameter values are generated from a so-called baseline prior...

Persistent link: https://www.econbiz.de/10011383033

An Alternative Bayesian Approach to Structural Breaks in Time Series Models

van den Hauwe, Sjoerd - 2011

Persistent link: https://www.econbiz.de/10013130370

Monitoring multicountry macroeconomic risk

Korobilis, Dimitris; Schröder, Maximilian - 2023

We propose a multicountry quantile factor augmeneted vector autoregression (QFAVAR) to model heterogeneities both across countries and across characteristics of the distributions of macroeconomic time series. The presence of quantile factors allows for summarizing these two heterogeneities in a...

Persistent link: https://www.econbiz.de/10014314068

Estimating (Markov-Switching) VAR Models Without Gibbs Sampling : A Sequential Monte Carlo Approach

Bognanni, Mark - 2015

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

Robust estimation of nonstationary, fractionally integrated, autoregressive, stochastic volatility

Jensen, Mark J. - 2015

Empirical volatility studies have discovered nonstationary, long-memory dynamics in the volatility of the stock market and foreign exchange rates. This highly persistent, infinite variance - but still mean reverting - behavior is commonly found with nonparametric estimates of the fractional...

Persistent link: https://www.econbiz.de/10011382237

A flexible predictive density combination for large financial data sets in regular and crisis periods

Casarin, Roberto; Grassi, Stefano; Ravazzolo, Francesco; … - 2022

A flexible predictive density combination is introduced for large financial data sets which allows for model set incompleteness. Dimension reduction procedures that include learning allocate the large sets of predictive densities and combination weights to relatively small subsets. Given the...

Persistent link: https://www.econbiz.de/10013332662

Estimating (Markov-switching) VAR models without Gibbs sampling : a sequential Monte Carlo approach

Bognanni, Mark; Herbst, Edward P. - 2015 - This draft: December 10, 2015

Vector autoregressions with Markov-switching parameters (MS-VARs) fit the data better than do their constant-parameter predecessors. However, Bayesian inference for MS-VARs with existing algorithms remains challenging. For our first contribution, we show that Sequential Monte Carlo (SMC)...

Persistent link: https://www.econbiz.de/10011499604