EconBase
← All papers

Triple the gamma -- A unifying shrinkage prior for variance and variable selection in sparse state space and TVP models

Annalisa Cadonna, Sylvia Frühwirth-Schnatter, Peter Knaus

arXiv 6 Dec 2019 · Econometrics · publishedEconometrics (2020) · 8 citations (OpenAlex)

arXiv:1912.03100 · PDF · DOI · OpenAlex · Extracted main text

Abstract

Time-varying parameter (TVP) models are very flexible in capturing gradual changes in the effect of a predictor on the outcome variable. However, in particular when the number of predictors is large, there is a known risk of overfitting and poor predictive performance, since the effect of some predictors is constant over time. We propose a prior for variance shrinkage in TVP models, called triple gamma. The triple gamma prior encompasses a number of priors that have been suggested previously, such as the Bayesian lasso, the double gamma prior and the Horseshoe prior. We present the desirable properties of such a prior and its relationship to Bayesian Model Averaging for variance selection. The features of the triple gamma prior are then illustrated in the context of time varying parameter vector autoregressive models, both for simulated datasets and for a series of macroeconomics variables in the Euro Area.

Citation extraction

54
references
104
in-text mentions
54
distinct cited
0
self-citations
13,817
main-text words

appendix boundary found by appendix_command · 82% of the source is main text. Read the extracted text to check this.

Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Bitto, A.; Frühwirth-Schnatter, S (2019) Achieving Shrinkage in a Time-Varying Parameter Model Framework1.000144100%
2Carvalho, C.M.; Polson, N.G.; Scott, J.G (2009) Handling sparsity via the horseshoe1.00054100%
3Belmonte, M.A.G.; Koop, G.; Korobolis, D (2014) Hierarchical shrinkage in time-varying parameter models0.92843100%
4Frühwirth-Schnatter, S.; Wagner, H (2010) Stochastic Model Specification Search for Gaussian and partially Non-Gaussian State Space Models0.92843100%
5Griffin, J.E.; Brown, P.J (2017) Hierarchical Shrinkage Priors for Regression Models0.92843100%
6Carvalho, C.M.; Polson, N.G.; Scott, J.G (2010) The horseshoe estimator for sparse signals0.84333100%
7Armagan, A.; Dunson, D.B.; Clyde, M (2011) Generalized beta mixtures of Gaussians0.73732100%
8Carriero, A.; Clark, T.G.; Marcellino, M (2019) Large Bayesian vector autoregressions with stochastic volatility and non-conjugate priors0.73732100%
9Bhadra, A.; Datta, J.; Polson, N.G.; Willard, B Lasso meets horsheshoe: A survey0.64422100%
10Chan, J.C.; Eisenstat, E (2016) Bayesian model comparison for time-varying parameter VARs with stochastic volatilty0.64422100%

Showing the top 10 of 54 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
10.54cm Time-Varying Parameters as Ridge Regressions1.00064
2The Dynamic Triple Gamma as a Shrinkage Process for Time-Varying Parameter Models0.928107
3Generalized Cumulative Shrinkage Process Priors with Applications to Sparse Bayesian Factor Analysis0.84333
4Partial Identification of Structural Vector Autoregressions with Non-Centred Stochastic Volatility0.73732
5Joint Quantile Shrinkage: A State-Space Approach toward Non-Crossing Bayesian Quantile Models0.51121
6Markov Switching0.40511
7The ARR2 prior: flexible predictive prior definition for Bayesian auto-regressions0.40511
8Bayesian State-Space Modeling and Model-Based Counterfactual Analysis of Dynamic Income Distributions from Grouped Data0.40511