Bayesian stochastic search for VAR model restrictions

By Edward I. George, Dongchu Sun, Shawn Ni. 2008

293 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/d4127a31c5b1a4be3a43e768680112fa80bf790f

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In Economics and Econometrics

In Management Science and Operations Research

Citations in the corpus

Model Averaging and Its Use in Economics (2017, methodology): “George et al. (2008) apply BMA ideas in VARs using SSVS methods with priors which do not induce exact zero restrictions on the coefficients, as in George and McCulloch (1993).”
Polynomial nonlinear spatio‐temporal integro‐difference equation models (2011, background): “For example, in the context of econometrics, George et al. (2008) proposed a Markov chain Monte Carlo (MCMC) algorithm that selects elements of both the VAR regression coefficient and the error variance matrices.”
Stochastic modelling for quantitative description of heterogeneous biological systems (2009, methodology): “This is a promising new area for research, and I believe that there will be important developments in the next year or two, including fully Bayesian approaches to the problem, inspired by related work in other application areas, such as econometric”
Granger Causality: A Review and Recent Advances (2021, methodology): “For instance, George et al. (2008) proposed a Bayesian stochastic search algorithm to identify high-dimensional VAR processes, whereas Ba´nbura et al. (2010) showed that better performance can be achieved in large models if the tightness of the priors is increased as the model size increases.”
Adaptive Shrinkage in Bayesian Vector Autoregressive Models (2019, methodology): “,m, follow a Gaussian distribution given by (George et al., 2008),”
Forecasting with Bayesian Vector Autoregression (2013, unknown): “George et al. (2008) suggests a semiautomatic choice with τ0,ij = σ̂γij/10 and τ1,ij = 10σ̂γijwhere σ̂γij is the standard error of the OLS estimate of γij in the unrestricted model.”
Time-Varying Effect of Oil Market Shocks on the Stock Market (2015, unknown): “This approach is regarded as a special form of Bayesian model stochastic search method to selecting restrictions for VAR models (for example see George and McCulloch (1997), George et al. (2008), Jochmann et al. (2010), and Jochmann et al. (2013)).”
Bayesian Multivariate Time Series Methods for Empirical Macroeconomics (2010, unknown): “Geweke and Keane, 2007, uses cross-validation). However, for the researcher who wishes to use marginal likelihoods, note that there are many methods for calculating them that involve the evaluation of the likelihood function at a point. For instance, information criteria are often approximations to ”
Time Varying Dimension Models (2012, unknown): “See, among many others, Banbura, Giannone, and Reichlin ( 2010 ), De Mol, Giannone, and Reichlin ( 2008 ), George, Sun, and Ni ( 2008 ), Korobilis ( 2011 ), Koop, Leon-Gonzalez, and Strachan ( 2009 ), and Groen, Paap, and Ravazzolo ( 2010 ).”