Changing Impact of Shocks: A Time‐Varying Proxy SVAR Approach
扩展了贝叶斯代理向量自回归模型，引入参数时变性，并用新算法估计美英税收冲击对产出增长影响的下降趋势。
Abstract In this paper, we extend the Bayesian Proxy vector autoregression (VAR) model to incorporate time variation in the parameters. A novel Metropolis‐within‐Gibbs sampling algorithm is provided to approximate the posterior distributions of the model's parameters. Using the proposed algorithm, we estimate the time‐varying effects of taxation shocks in the United States and the United Kingdom and find evidence for a decline in the impact of these shocks on output growth.