Time-varying sparsity in dynamic regression models

DOI10.1016/J.JECONOM.2013.10.012zbMath1293.62191OpenAlexW2034370155MaRDI QIDQ2512529

Maria Kalli, Jim E. Griffin

Publication date: 7 August 2014

Published in: Journal of Econometrics (Search for Journal in Brave)

Full work available at URL: http://create.canterbury.ac.uk/12075/1/dynamic_sparsity_rev.pdf

zbMATH Keywords

Markov chain Monte Carloinflationequity premiumshrinkage priorstime-varying regressionnormal-gamma priors

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Linear regression; mixed models (62J05) Bayesian inference (62F15)

Related Items (9)

An adaptive truncation method for inference in Bayesian nonparametric models ⋮ Parsimony inducing priors for large scale state-space models ⋮ Bayesian Approaches to Shrinkage and Sparse Estimation ⋮ Relevant parameter changes in structural break models ⋮ BAYESIAN DYNAMIC VARIABLE SELECTION IN HIGH DIMENSIONS ⋮ Achieving shrinkage in a time-varying parameter model framework ⋮ Complete subset regressions ⋮ Dynamic variable selection with spike-and-slab process priors ⋮ Specification tests for time-varying parameter models with stochastic volatility

Uses Software

• bvarsv

Cites Work

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