Estimating Posterior Sensitivities with Application to Structural Analysis of Bayesian Vector Autoregressions
后验敏感性的估计及其在贝叶斯 VAR 结构分析中的应用
The inherent feature of Bayesian empirical analysis is the dependence of posterior inference on prior parameters, which researchers typically specify.However, quantifying the magnitude of this dependence remains difficult.This article extends Infinitesimal Perturbation Analysis, widely used in classical simulation, to compute asymptotically unbiased and consistent sensitivities of posterior statistics with respect to prior parameters from Markov chain Monte Carlo inference…