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The Beveridge-Nelson decomposition of mixed-frequency series: An application to simultaneous measurement of classical and deviation cycles

机译:混合频率序列的Beveridge-Nelson分解:同时测量经典周期和偏差周期的应用

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摘要

Gibbs sampling for Bayesian VAR with mixed-frequency series draws latent high-frequency series and model parameters sequentially. Applying the multivari-ate Beveridge-Nelson (B-N) decomposition in each Gibbs step, one can simulate the joint posterior distribution of the B-N permanent and transitory components in latent and observable high-frequency series. This paper applies the method to mixed-frequency series of macroeconomic variables including quarterly real GDP to estimate the monthly natural rates and gaps of output, inflation, interest, and unemployment jointly. The resulting monthly real GDP and GDP gap are complementary coincident indices, measuring classical and deviation cycles, respectively.
机译:混合频率序列的贝叶斯VAR的Gibbs采样顺序绘制了潜在的高频序列和模型参数。在每个吉布斯步骤中应用多元Beveridge-Nelson(B-N)分解,可以模拟潜在和可观察的高频序列中B-N永久分量和过渡分量的联合后验分布。本文将该方法应用于包括季度实际GDP在内的宏观经济变量的混合频率序列,以共同估算月度自然率以及产出,通货膨胀,利息和失业率的缺口。由此产生的每月实际GDP和GDP差距是互补的一致指数,分别测量经典周期和偏离周期。

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