ESTIMATING MULTICOUNTRY VAR MODELS*
提出一种贝叶斯方法，用于估计包含跨国依赖、各国特有动态和系数时变的多国向量自回归模型，并通过MCMC进行推断和政策分析。
This article presents a method to estimate the coefficients, to test specification hypotheses, and to conduct policy exercises in multicountry Vector Autoregressive (VAR) models with cross‐unit interdependencies, unit‐specific dynamics, and time variations in the coefficients. The framework of analysis is Bayesian: A prior flexibly reduces the dimensionality of the model and puts structure on the time variations, Markov chain Monte Carlo (MCMC) methods are used to obtain posterior distributions, and marginal likelihoods to check the fit of various specifications. Impulse responses and conditional forecasts are obtained with the output of an MCMC routine. The transmission of certain shocks across countries is analyzed.